2470 Snowflake Jobs - Page 19

Job Role: Data Quality Integration Engineer Location: PAN India Role Overview As a Data Quality Integration Engineer, you will be responsible for embedding data quality capabilities across enterprise data landscapes. You will lead the integration of advanced data quality tools such as Ataccama and Collibra with cloud data platforms like Snowflake and SQL databases. This role is essential in ensuring our data governance standards are met with robust, scalable, and automated data quality processes. Role Proficiency Develop scalable applications using suitable technical options. Optimize application development, maintenance, and performance. Reuse proven design patterns and manage peer development activities. Key Responsibilities Technical & Functional Responsibilities Design and implement integration of data quality tools (Ataccama, Collibra, etc.) with Snowflake and SQL-based platforms. Develop automated pipelines and connectors for profiling, cleansing, monitoring, and validating data. Configure and manage data quality rules and workflows aligned to governance policies and KPIs. Troubleshoot integration issues, monitor performance, and optimize reliability and efficiency. Collaborate with Data Governance, Architecture, and Engineering teams to align solutions with business needs. Maintain comprehensive documentation for integration solutions and configurations. Software Engineering Deliverables Code : Adhere to coding standards, perform peer reviews, and write optimized code. Documentation : Create/review design documents, templates, test cases, and checklists. Testing : Develop/review unit and integration test cases; support QA teams. Configuration : Define and manage configuration management practices. Release : Execute and oversee release processes. Project & Team Management Estimate efforts for project deliverables and track timelines. Perform defect RCA, trend analysis, and propose quality improvements. Set and review FAST goals for self and team. Mentor team members, manage aspirations, and keep the team engaged. Key Outcomes & Metrics Timely adherence to engineering and project standards. Minimal post-delivery defects and technical issues. Compliance with mandatory training and documentation processes. Increased customer satisfaction and domain relevance. Skills & Technologies Mandatory Skills Strong experience with data quality tools (Ataccama, Collibra). Hands-on with Snowflake and SQL databases (e.g., PostgreSQL, SQL Server, Oracle). Proficient in SQL scripting and data pipeline development (Python or Scala preferred). Sound understanding of data profiling, cleansing, enrichment, and monitoring. Familiar with REST APIs and metadata integration techniques. Desirable Skills Experience in cloud platforms (AWS, Azure) hosting Snowflake. Certification in Collibra, Ataccama, or Snowflake. Exposure to financial services or regulated industries. Prior involvement in data stewardship/governance initiatives. Soft Skills Strong analytical and problem-solving abilities. Ability to manage high-pressure environments and multiple priorities. Effective communication and presentation skills. Ability to mentor and guide junior engineers. Business etiquette in professional interactions. Certifications (Preferred) Ataccama/Collibra Certified Professional Snowflake Architect/Developer Certification AWS/Azure Data Engineering Certifications Domain Knowledge Deep understanding of enterprise data architecture and governance. Knowledge of financial services, insurance, or asset management domains is an advantage.

Role Description: As a Data Engineering Lead, you will play a crucial role in overseeing the design, development, and maintenance of our organization's data architecture and infrastructure. You will be responsible for designing and developing the architecture for the data platform that ensures the efficient and effective processing of large volumes of data, enabling the business to make informed decisions based on reliable and high-quality data. The ideal candidate will have a strong background in data engineering, excellent leadership skills, and a proven track record of successfully managing complex data projects. Responsibilities : Data Architecture and Design : Design and implement scalable and efficient data architectures to support the organization's data processing needs Work closely with cross-functional teams to understand data requirements and ensure that data solutions align with business objectives ETL Development : Oversee the development of robust ETL processes to extract, transform, and load data from various sources into the data warehouse Ensure data quality and integrity throughout the ETL process, implementing best practices for data cleansing and validation Big Data Technology - Stay abreast of emerging trends and technologies in big data and analytics, and assess their applicability to the organization's data strategy Implement and optimize big data technologies to process and analyze large datasets efficiently Cloud Integration: Collaborate with the IT infrastructure team to integrate data engineering solutions with cloud platforms, ensuring scalability, security, and performance. Performance Monitoring and Optimization : Implement monitoring tools and processes to track the performance of data pipelines and proactively address any issues Optimize data processing. Documentation : Maintain comprehensive documentation for data engineering processes, data models, and system architecture Ensure that team members follow documentation standards and best practices. Collaboration and Communication : Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and deliver solutions that meet those requirements Communicate effectively with technical and non-technical stakeholders, providing updates on project status, challenges, and opportunities. Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. 6-8 years of professional experience in data engineering In-depth knowledge of data modeling, ETL processes, and data warehousing. In-depth knowledge of building the data warehouse using Snowflake Should have experience in data ingestion, data lakes, data mesh and data governance Must have experience in Python programming Strong understanding of big data technologies and frameworks, such as Hadoop, Spark, and Kafka. Experience with cloud platforms, such as AWS, Azure, or Google Cloud. Familiarity with database systems like SQL, NoSQL, and data pipeline orchestration tools .Excellent problem-solving and analytical skills .Strong communication and interpersonal skills. Proven ability to work collaboratively in a fast-paced, dynamic environment.

Design, develop, and optimize ETL/ELT pipelines for data ingestion, transformation, and loading using Snowflake. Build and maintain scalable and robust data warehousing solutions. Work closely with data architects, analysts, and business stakeholders to gather requirements and deliver solutions. Optimize Snowflake performance by managing clusters, warehouses, and query tuning. Monitor data pipelines and troubleshoot any issues related to data ingestion or transformation. Implement data security, governance, and compliance best practices within the Snowflake environment. Write complex SQL queries and stored procedures for data manipulation and reporting. Collaborate with BI and analytics teams to support data extraction and reporting needs. Document processes, architecture, and best practices. Required Skills: Strong experience with Snowflake data platform (warehouses, micro-partitions, streams, tasks). Expertise in ETL tools and frameworks (e.g., Talend, Informatica, Apache NiFi, or native Snowflake tasks). Proficient in SQL and performance tuning. Experience with data modeling and dimensional modeling techniques. Familiarity with cloud platforms like AWS, Azure, or GCP is a plus. Good understanding of data governance, data security, and compliance. Strong analytical, problem-solving, and communication skills. Role & responsibilities Preferred candidate profile

Develop and maintain cloud-based data pipelines using tools like Apache Airflow or AWS Glue Support ETL processes and ensure data quality and consistency Monitor and troubleshoot cloud infrastructure performance Implement data security & compliance

Role & responsibilities We are looking for Sr. Snowflake developer for Bangalore - Hybrid (2 days WFO) someone with 7+ YOE in Snowflake, Stored procedures, Python, & cloud.

About the Role We are looking for an Analytics Engineer with 2+ years of experience to help build and maintain our modern data platform. You'll work with dbt , Snowflake , and Airflow to develop clean, well-documented, and trusted datasets. This is a hands-on role ideal for someone who wants to grow their technical skills while contributing to a high-impact analytics function. Key Responsibilities Build and maintain scalable data models using dbt and Snowflake Develop and orchestrate data pipelines with Airflow or similar tools Partner with teams across DAZN to translate business needs into robust datasets Ensure data quality through testing, validation, and monitoring practices Follow best practices in code versioning, CI/CD, and data documentation Contribute to the evolution of our data architecture and team standards What Were Looking For 2+ years of experience in analytics/data engineering or similar roles Strong skills in SQL and working knowledge of cloud data warehouses (Snowflake preferred) Experience with dbt for data modeling and transformation Familiarity with Airflow or other workflow orchestration tools Understanding of ELT processes, data modeling, and data governance principles Strong collaboration and communication skills Nice to Have Experience working in media, OTT, or sports technology domains Familiarity with BI tools like Looker , Tableau , or Power BI Exposure to testing frameworks like dbt tests or Great Expectations

Duration of contract* 12 months (might get extended) Total Yrs. of Experience* 12+ for Sr. Developer , 8+ for Mid level developer Relevant Yrs. of experience* 8+ for Sr. Developer , 4 for Mid level developer Detailed JD *(Roles and Responsibilities) Technical Leadership & Development: - Design, build, and optimize scalable data pipelines using Snowflake, DBT, and related technologies. - Oversee the end-to-end architecture and development of ELT/ETL processes and data models. - Collaborate with data analysts, business analysts, customer leads, and business stakeholders to translate requirements into data solutions. - Lead complex data ingestion and transformation workflows using DBT (modular SQL, Jinja, macros). - Ensure performance tuning, resource optimization, and cost-efficiency in Snowflake environments. Team Leadership: - Lead and mentor a team of 45 data engineers. - Define and enforce best practices for coding, testing, and deployment in data engineering projects. - Conduct code reviews, knowledge sharing, and skills development sessions. - Manage team workload, priorities, and delivery timelines using Agile methodologies. Stakeholder Collaboration: - Work closely with GBS delivery leads, business SMEs, and data engineering teams. - Communicate technical solutions effectively to both technical and non-technical stakeholders. - Contribute to roadmap planning and architectural decisions. Mandatory skills* Technical: - 5+ years of hands-on experience with Snowflake (data modeling, SnowSQL, performance tuning). - 3+ years of production experience with DBT (Data Build Tool) for data transformations. - Proficiency in SQL, data modeling, and cloud platforms (AWS). - Experience in building modular data models (star/snowflake schemas, fact/dimension tables). - Strong understanding of data governance, security, and compliance principles. Leadership: - Proven experience in leading data engineering teams and delivering enterprise-grade solutions. - Strong understanding of project management and Agile delivery skills (Jira, Confluence, Git). - Ability to mentor junior engineers and create a culture of continuous improvement. Desired skills* Preferred Qualifications: - Snowflake SnowPro certification. - DBT certification. - Experience with orchestration tools (e.g., Airflow, Prefect). - Familiarity with CI/CD pipelines for data infrastructure. - Exposure to data quality frameworks and observability tools. Domain* LS Precise Work Location* Pan India

Job Summary We are seeking an experienced Data Architect with expertise in Snowflake, dbt, Apache Airflow, and AWS to design, implement, and optimize scalable data solutions. The ideal candidate will play a critical role in defining data architecture, governance, and best practices while collaborating with cross-functional teams to drive data-driven decision-making. Key Responsibilities Data Architecture & Strategy: Design and implement scalable, high-performance cloud-based data architectures on AWS. Define data modelling standards for structured and semi-structured data in Snowflake. Establish data governance, security, and compliance best practices. Data Warehousing & ETL/ELT Pipelines: Develop, maintain, and optimize Snowflake-based data warehouses. Implement dbt (Data Build Tool) for data transformation and modelling. Design and schedule data pipelines using Apache Airflow for orchestration. Cloud & Infrastructure Management: Architect and optimize data pipelines using AWS services like S3, Glue, Lambda, and Redshift. Ensure cost-effective, highly available, and scalable cloud data solutions. Collaboration & Leadership: Work closely with data engineers, analysts, and business stakeholders to align data solutions with business goals. Provide technical guidance and mentoring to the data engineering team. Performance Optimization & Monitoring: Optimize query performance and data processing within Snowflake. Implement logging, monitoring, and alerting for pipeline reliability. Required Skills & Qualifications 10+ years of experience in data architecture, engineering, or related roles. Strong expertise in Snowflake, including data modeling, performance tuning, and security best practices. Hands-on experience with dbt for data transformations and modeling. Proficiency in Apache Airflow for workflow orchestration. Strong knowledge of AWS services (S3, Glue, Lambda, Redshift, IAM, EC2, etc.). Experience with SQL, Python, or Spark for data processing. Familiarity with CI/CD pipelines, Infrastructure-as-Code (Terraform/CloudFormation) is a plus. Strong understanding of data governance, security, and compliance (GDPR, HIPAA, etc.). Preferred Qualifications Certifications: AWS Certified Data Analytics Specialty, Snowflake SnowPro Certification, or dbt Certification. Experience with streaming technologies (Kafka, Kinesis) is a plus. Knowledge of modern data stack tools (Looker, Power BI, etc.). Experience in OTT streaming could be added advantage.

Hexaware Technologies is Hiring Snowflake developers Primary Skill set - Snowflake, Data warehousing Total Exp Required - 6 + years to 12yrs Location - Chennai, Mumbai, Pune, Bangalore Work mode - Hybrid Job Description: Snowflake Data Engineer As a Snowflake Data Engineer, you will be responsible for designing, developing, and maintaining our Snowflake data warehouse. You will work closely with data analysts, data scientists, and other stakeholders to ensure data integrity, optimize performance, and support data-driven decision-making processes. Key Responsibilities : • Design and implement scalable data pipelines in Snowflake. • Develop and maintain ETL processes to ingest data from various sources into Snowflake. • Optimize and tune Snowflake queries for performance. • Ensure data quality and integrity through data validation and cleansing. • Collaborate with data analysts and data scientists to understand data requirements and provide necessary support. • Monitor and troubleshoot data pipeline and Snowflake performance issues. • Implement data security and compliance measures in accordance with company policies. • Stay updated with the latest trends and best practices in Snowflake and data engineering. Requirements: • 7+ years of experience in data engineering or a similar role. • Strong experience with Snowflake data warehouse. • Proficiency in Oracle (PL/SQL) • Experience with ETL tools (e.g., Apache NiFi, Talend, Informatica). • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud). • Experience with data modeling and schema design. • Strong problem-solving skills and attention to detail. • Excellent communication and collaboration skills. Preferred Qualifications: • Snowflake certification. • Experience with Python or other programming languages. • Knowledge of data visualization tools (e.g., Tableau, Power BI). • Experience with data governance and data cataloging tools. Interested candidates, Kindly share your updated resume to ramyar2@hexaware.com with below required details. Full Name: Contact No: Total Exp: Rel Exp in Snowflake & DWH: Current & Joining Location: Notice Period (If serving mention LWD): Current CTC: Expected CTC:

Role & responsibilities .Mastery of SQL, especially within cloud-based data warehouses like Snowflake. Experience on Snowflake with data architecture, design, analytics and Development. 2.Detailed knowledge and hands-on working experience in Snowpipe/ SnowProc/ SnowSql. 3.Technical lead with strong development background having 2-3 years of rich hands-on development experience in snowflake. 4.Experience designing highly scalable ETL/ELT processes with complex data transformations, data formats including error handling and monitoring. Good working knowledge of ETL/ELT tool DBT for transformation 5.Analysis, design, and development of traditional data warehouse and business intelligence solutions. Work with customers to understand and execute their requirements. 6.Working knowledge of software engineering best practices. Should be willing to work in implementation & support projects. Flexible for Onsite & Offshore traveling. 7.Collaborate with other team members to ensure the proper delivery of the requirement. Ability to think strategically about the broader market and influence company direction. 8.Should have good communication skills, team player & good analytical skills. Snowflake certified is preferable. Contact Soniya soniya05.mississippiconsultants@gmail.com

We are looking for an experienced Data Modelling professional, proficient in tools such as Erwin and ER/Studio. A strong understanding of Azure Databricks, Snowflake/Redshift, SAP HANA, and advanced SQL is required. Prior experience in leading teams is also preferred.

About the Role: Grade Level (for internal use): 10 The Team: We seek a highly motivated, enthusiastic, and skilled engineer for our Industry Data Solutions Team. We strive to deliver sector-specific, data-rich, and hyper-targeted solutions for evolving business needs. You will be expected to participate in the design review process, write high-quality code, and work with a dedicated team of QA Analysts and Infrastructure Teams. The Impact: Enterprise Data Organization is seeking a Software Developer to create software design, development, and maintenance for data processing applications. This person would be part of a development team that manages and supports the internal & external applications that is supporting the business portfolio. This role expects a candidate to handle any data processing, big data application development. We have teams made up of people that learn how to work effectively together while working with the larger group of developers on our platform. Whats in it for you: Opportunity to contribute to the development of a world-class Platform Engineering team . Engage in a highly technical, hands-on role designed to elevate team capabilities and foster continuous skill enhancement. Be part of a fast-paced, agile environment that processes massive volumes of dataideal for advancing your software development and data engineering expertise while working with a modern tech stack. Contribute to the development and support of Tier-1, business-critical applications that are central to operations. Gain exposure to and work with cutting-edge technologies, including AWS Cloud and Databricks . Grow your career within a globally distributed team , with clear opportunities for advancement and skill development. Responsibilities: Design and develop applications, components, and common services based on development models, languages, and tools, including unit testing, performance testing, and monitoring, and implementation Support business and technology teams as necessary during design, development, and delivery to ensure scalable and robust solutions Build data-intensive applications and services to support and enhance fundamental financials in appropriate technologies.( C#, .Net Core, Databricsk ,Python, Scala, NIFI , SQL) Build data modeling, achieve performance tuning and apply data architecture concepts Develop applications adhering to secure coding practices and industry-standard coding guidelines, ensuring compliance with security best practices (e.g., OWASP) and internal governance policies. Implement and maintain CI/CD pipelines to streamline build, test, and deployment processes; develop comprehensive unit test cases and ensure code quality Provide operations support to resolve issues proactively and with utmost urgency Effectively manage time and multiple tasks Communicate effectively, especially in writing, with the business and other technical groups Basic Qualifications: Bachelor's/Masters Degree in Computer Science, Information Systems or equivalent. Minimum 5 to 8 years of strong hand-development experience in C#, .Net Core, Cloud Native, MS SQL Server backend development. Proficiency with Object Oriented Programming. Nice to have knowledge in Grafana, Kibana, Big data, Git Hub, EMR, Terraforms, AI-ML Advanced SQL programming skills Highly recommended skillset in Databricks , Scalatechnologies. Understanding of database performance tuning in large datasets Ability to manage multiple priorities efficiently and effectively within specific timeframes Excellent logical, analytical and communication skills are essential, with strong verbal and writing proficiencies Knowledge of Fundamentals, or financial industry highly preferred. Experience in conducting application design and code reviews Proficiency with following technologies: Object-oriented programming Programing Languages (C#, .Net Core) Cloud Computing Database systems (SQL, MS SQL) Nice to haveNo-SQL (Databricks, Scala, python), Scripting (Bash, Scala, Perl, Powershell) Preferred Qualifications: Hands-on experience with cloud computing platforms including AWS , Azure , or Google Cloud Platform (GCP) . Proficient in working with Snowflake and Databricks for cloud-based data analytics and processing. Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, pre-employment training or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here. ---- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. 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Work Hours: 4:30 PM to 1:30 AM IST Experience Required: 8+ Years Role Summary: We are seeking an experienced DBT Engineer with good experience in Azure Cloud , DBT (Data Build Tool) , and Snowflake . The ideal candidate will have a good background in building scalable data pipelines, designing efficient data models, and enabling advanced analytics. Key Responsibilities: Design and maintain scalable ETL pipelines with DBT and SQL , ensuring high performance and reliability. Develop advanced DBT workflows using artifact files, graph variables, and complex macros leveraging run_query. Implement multi-repo or mesh DBT setups to support scalable and collaborative workflows. Utilize DBT Cloud features such as documentation, Explorer, CLI, and orchestration to optimize data processes. Build and manage CI/CD pipelines to automate and enhance data deployment processes. Write and optimize complex SQL queries to transform large datasets and ensure data accuracy. Collaborate with cross-functional teams to integrate data solutions into existing workflows. Troubleshoot and resolve errors in pipelines caused by DBT code or transformation issues. Adhere to best practices for version control using git flow workflows to manage and deploy code changes. Ensure code quality and maintainability by implementing code linting and conducting code reviews. Required Skills and Qualifications: 8+ years of experience in data engineering with a strong focus on ETL processes and data pipeline management. MUST have experience in Azure cloud, working on Data warehousing involving ADF, Azure Data Lake, DBT and Snowflake At least 4+ years of hands-on experience with DBT . Advanced proficiency in SQL and data modeling techniques . Deep understanding of DBT, including artifact files, graph usage, and MetricFlow. Proficiency in DBT Cloud features like CLI, orchestration, and documentation. Strong skills in Python for scripting and automation tasks. Familiarity with CI/CD pipeline tools and workflows. Hands-on experience with git flow workflows for version control. Solid troubleshooting skills to resolve pipeline errors efficiently. Knowledge of pipeline orchestration and automation. Soft Skills: A proactive problem-solver with excellent attention to detail. Strong communication and collaboration skills to work with cross-functional teams. A positive attitude and ownership mindset to drive projects to completion.

Roles: Design and optimise Snowflake data architectures for AI and analytics. Develop scalable OLAP models for real-time and customer insights. Collaborate with AI, engineering, and product teams. Drive data governance, security, and performance. Annual bonus

Overview Enterprise Data Operations Analyst Job OverviewAs an Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks , Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/ modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives , maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ , and Great Expectations. Experience building/ operating highly available , distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake . Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI ).

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview This person will look after the environment management of the salesforce orgs and will also be able to handle the deployments within multiple salesforce orgs. Responsibilities Oversee Salesforce Data Cloud environments across development, staging, and production. Define best practices for environment setup, security, and governance. Manage data pipelines, ingestion processes, and harmonization rules for efficient data flow. Establish role-based access control (RBAC) to ensure data security and compliance. Monitor data processing jobs, ingestion performance, and data harmonization. Ensure compliance with GDPR, CCPA, and other data privacy regulations Establish CI/CD pipelines using tools like Azure DevOps Implement version control and automated deployment strategies for Data Cloud configurations Define a data refresh strategy for lower environments to maintain consistency. Qualifications Mandatory Technical Skills Extensive experience in setting up, maintaining, and troubleshooting CI/CD pipelines for Salesforce apps. Strong knowledge of Azure DevOps tools and pipeline creation, with proficiency in automation scripting (primarily YAML, with additional languages as needed). Hands-on experience with SFDX, Azure Repos, and automated release deployments for Salesforce. Expertise in implementing GIT branching strategies using VS Code integrated with Salesforce CLI tool. Mandatory Skills Proficiency in Salesforce Data Cloud architecture and best practices. Experience with data lake, Snowflake, or cloud-based data storage solutions. Familiarity with OAuth, authentication mechanisms, and data security standards. Salesforce Data Cloud Consultant Certification

Overview As a member of the Platform engineering team, you will be the key techno functional expert leading and overseeing PepsiCo's Platforms & operations and drive a strong vision for how Platforms engineering can proactively create a positive impact on the business. You'll be an empowered Leader of a team of Platform engineers who build Platform products for platform optimization and cost optimization and build tools for Platform ops and Data Ops on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As Leader of the Platform engineering team, you will help in managing platform Governance team that builds frameworks to guardrail the platforms of very large and complex data applications in public cloud environments and directly impact the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Active contributor to cost optimization of platforms and services. Manage and scale Azure Data Platforms to support new product launches and drive Platform Stability and Observability across data products. Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for Data Platforms for cost and performance. Responsible for implementing best practices around systems integration, security, performance and Platform management. Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape. Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions. Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners. Develop and optimize procedures to production Alize data science models. Define and manage SLAs for Platforms and processes running in production. Support large-scale experimentation done by data scientists. Prototype new approaches and build solutions at scale. Research in state-of-the-art methodologies. Create documentation for learnings and knowledge transfer. Create and audit reusable packages or libraries. Qualifications 10+ years of overall technology experience that includes at least 4+ years of hands-on software development, Program management, and Advanced Analytics. 4+ years of experience with Power BI, Tableau, Data Warehousing, and Data Analytics tools. 4+ years of experience in Platform optimization and performance tuning Experience in managing multiple teams and coordinating with different stakeholders to implement the vision of the team. Fluent with Azure cloud services. Azure Certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Experience with data modeling, data warehousing, and building Symantec Models. Proficient in DAX queries, Copilot and AI Skills Experience building/operating highly available, distributed systems of data Visualization . Experience with at least one MPP database technology such as Redshift, Synapse or Snowflake. Experience with version control systems like Github and deployment & CI tools. Knowledge of Azure Data Factory, Azure Databricks. Experience with Statistical/ML techniques is a plus. Experience with building solutions in the retail or in the supply chain space is a plus Understanding of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with Augmented Analytics tools is Plus (such as ThoughtSpot, Tellius).

Overview As an Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 4+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview Enterprise Data Operations Sr Analyst L08 Job OverviewAs Senior Analyst, Data Modeling , your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics . The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks , Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/ modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives , maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ , and Great Expectations. Experience building/ operating highly available , distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake . Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI ). Does the person hired for this job need to be based in a PepsiCo office, or can they be remote Employee must be based in a Pepsico office Primary Work LocationHyderabad HUB-IND

Overview As an Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data streaming (consumption/production), data in-transit. Develop reusable data models based on cloud-centric, code-first approaches to data management and cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 5+ years of overall technology experience that includes at least 2+ years of data modeling and systems architecture. Around 2+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 2+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Overview As Senior Analyst, Data Modeling, your focus would be to partner with D&A Data Foundation team members to create data models for Global projects. This would include independently analyzing project data needs, identifying data storage and integration needs/issues, and driving opportunities for data model reuse, satisfying project requirements. Role will advocate Enterprise Architecture, Data Design, and D&A standards, and best practices. You will be performing all aspects of Data Modeling working closely with Data Governance, Data Engineering and Data Architects teams. As a member of the data modeling team, you will create data models for very large and complex data applications in public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. The primary responsibilities of this role are to work with data product owners, data management owners, and data engineering teams to create physical and logical data models with an extensible philosophy to support future, unknown use cases with minimal rework. You'll be working in a hybrid environment with in-house, on-premise data sources as well as cloud and remote systems. You will establish data design patterns that will drive flexible, scalable, and efficient data models to maximize value and reuse. Responsibilities Complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies. Governs data design/modeling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. Provides and/or supports data analysis, requirements gathering, solution development, and design reviews for enhancements to, or new, applications/reporting. Supports assigned project contractors (both on- & off-shore), orienting new contractors to standards, best practices, and tools. Contributes to project cost estimates, working with senior members of team to evaluate the size and complexity of the changes or new development. Ensure physical and logical data models are designed with an extensible philosophy to support future, unknown use cases with minimal rework. Develop a deep understanding of the business domain and enterprise technology inventory to craft a solution roadmap that achieves business objectives, maximizes reuse. Partner with IT, data engineering and other teams to ensure the enterprise data model incorporates key dimensions needed for the proper managementbusiness and financial policies, security, local-market regulatory rules, consumer privacy by design principles (PII management) and all linked across fundamental identity foundations. Drive collaborative reviews of design, code, data, security features implementation performed by data engineers to drive data product development. Assist with data planning, sourcing, collection, profiling, and transformation. Create Source To Target Mappings for ETL and BI developers. Show expertise for data at all levelslow-latency, relational, and unstructured data stores; analytical and data lakes; data str/cleansing. Partner with the Data Governance team to standardize their classification of unstructured data into standard structures for data discovery and action by business customers and stakeholders. Support data lineage and mapping of source system data to canonical data stores for research, analysis and productization. Qualifications 8+ years of overall technology experience that includes at least 4+ years of data modeling and systems architecture. 3+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools. 4+ years of experience developing enterprise data models. Experience in building solutions in the retail or in the supply chain space. Expertise in data modeling tools (ER/Studio, Erwin, IDM/ARDM models). Experience with integration of multi cloud services (Azure) with on-premises technologies. Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one MPP database technology such as Redshift, Synapse, Teradata or SnowFlake. Experience with version control systems like Github and deployment & CI tools. Experience with Azure Data Factory, Databricks and Azure Machine learning is a plus. Experience of metadata management, data lineage, and data glossaries is a plus. Working knowledge of agile development, including DevOps and DataOps concepts. Familiarity with business intelligence tools (such as PowerBI).

Bachelors degree or military experience in related field preferably computer science and 7 years of experience in ETL development within a Data Warehouse Deep understanding of enterprise data warehousing best practices and standards Strong experience in software engineering comprising of designing, developing and operating robust and highly scalable cloud infrastructure services Strong experience with Python/PySpark, DataStage ETL and SQL development Proven experience in cloud infrastructure projects with hands on migration expertise on public clouds such as AWS and Azure, preferably Snowflake Knowledge of Cybersecurity organization practices, operations, risk management processes, principles, architectural requirements, engineering and threats and vulnerabilities, including incident response methodologies Understand Authentication & Authorization Services, Identity & Access Management Strong communication and interpersonal skills

Job Title Data ArchitectExperience 10-12 YearsLocation Chennai : 10-12 years experience as Data Architect Strong expertise in streaming data technologies like Apache Kafka, Flink, Spark Streaming, or Kinesis. ProficiencyinprogramminglanguagessuchasPython,Java,Scala,orGo ExperiencewithbigdatatoolslikeHadoop,Hive,anddatawarehousessuchas Snowflake,Redshift,Databricks,MicrosoftFabric. Proficiencyindatabasetechnologies(SQL,NoSQL,PostgreSQL,MongoDB,DynamoDB,YugabyteDB). Should be flexible to work as anIndividual contributor

Highly skilled and experienced Data Modeler to join Enterprise Data Modelling team. The candidate will be responsible for creating and maintaining conceptual logical and physical data models ensuring alignment with industry best practices and standards. Working closely with business and functional teams the Data Modeler will play a pivotal role in standardizing data models at portfolio and domain levels driving efficiencies and maximizing the value of clients data assets. Preference will be given to candidates with prior experience within an Enterprise Data Modeling team. The ideal domain experience would be Insurance or Investment Banking. Roles and Responsibilities: Develop comprehensive conceptual logical and physical data models for multiple domains within the organization leveraging industry best practices and standards. Collaborate with business and functional teams to understand their data requirements and translate them into effective data models that support their strategic objectives. Serve as a subject matter expert in data modeling tools such as ERwin Data Modeler providing guidance and support to other team members and stakeholders. Establish and maintain standardized data models across portfolios and domains ensuring consistency governance and alignment with organizational objectives. Identify opportunities to optimize existing data models and enhance data utilization particularly in critical areas such as fraud banking AML. Provide consulting services to internal groups on data modeling tool usage administration and issue resolution promoting seamless data flow and application connections. Develop and deliver training content and support materials for data models ensuring that stakeholders have the necessary resources to understand and utilize them effectively. Collaborate with the enterprise data modeling group to develop and implement a robust governance framework and metrics for model standardization with a focus on longterm automated monitoring solutions. Qualifications: Bachelors or masters degree in computer science Information Systems or a related field. 10 years of experience working as a Data Modeler or in a similar role preferably within a large enterprise environment. Expertise in data modeling concepts and methodologies with demonstrated proficiency in creating conceptual logical and physical data models. Handson experience with data modeling tools such as Erwin Data Modeler as well as proficiency in database environments such as Snowflake and Netezza. Strong analytical and problemsolving skills with the ability to understand complex data requirements and translate them into effective data models. Excellent communication and collaboration skills with the ability to work effectively with crossfunctional teams and stakeholders. problem-solving skills,business intelligence platforms,erwin,data modeling,database management systems,data warehousing,etl processes,big data technologies,agile methodologies,data governance,sql,enterprise data modelling,data visualization tools,cloud data services,analytical skills,data modelling tool,,data architecture,communication skills