2658 Snowflake Jobs - Page 16

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Required Skills : Working knowledge of Big Data / cloud-based / columnar databases (such as Snowflake, AWS Redshift, Bigquery etc.) Experience in scripting languages like Python, R,Spark, Perl, etc. Very good knowledge of ETL concepts Experience in ETL tools like SSIS, Talend, Pentaho, etc., is a plus Very good knowledge of SQL querying Rich experience in relational data modelling Experience in developing logical, physical, and conceptual data models. Experience in AWS & Google cloud Services is a plus Experience with BI dashboard is plus Implementing automated testing platforms and unit tests Proficient understanding of code versioning tools, such as Git Strong analytical skills and problem-solving aptitude. Ability to learn new technologies quickly. Work with other team members in collaborative manner. Passionate to learn & work on versatile technologies Notice Period : Immediate 15 days

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience: 8-10 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies Database - PostgreSQL - PostgreSQL Database - Sql Server - SQL Packages ETL - ETL - Tester QA/QE - QA Automation - ETL Testing Beh - Communication

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. ________________________________________ Required Skills & Experience: Experience: 5-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies QA/QE - QA Automation - ETL Testing ETL - ETL - Tester Beh - Communication and collaboration Database - Sql Server - SQL Packages Database - PostgreSQL - PostgreSQL

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience: 5-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies QA/QE - QA Automation - ETL Testing ETL - ETL - Tester Beh - Communication and collaboration Database - Sql Server - SQL Packages Database - PostgreSQL - PostgreSQL

2-7 years of experience in software development. Solid background in GoLang. Strong data structures and algorithms concepts. Designing and problem-solving skills, with a strong bias for architecting for performance and scalability. Sound knowledge of cloud services and Kubernetes.

Job Summary: We are looking for a highly skilled Senior Data Engineer with expertise in Snowflake, DBT (Data Build Tool), and SAP Data Services (SAP DS). The ideal candidate will be responsible for building scalable data pipelines, designing robust data models, and ensuring high data quality across enterprise platforms. Key Responsibilities: Design, build, and optimize data pipelines and ETL/ELT workflows using Snowflake and DBT Integrate and manage data from various sources using SAP Data Services Develop and maintain scalable data models, data marts, and data warehouses Work closely with data analysts, business stakeholders, and BI teams to support reporting and analytics needs Implement best practices in data governance, data lineage, and metadata management Monitor data quality, troubleshoot issues, and ensure data integrity Optimize Snowflake data warehouse performance (partitioning, caching, query tuning) Automate data workflows and deploy DBT models with CI/CD tools (e.g., Git, Jenkins) Document architecture, data flows, and technical specifications

Job Summary: We are looking for a highly skilled Senior Data Engineer with expertise in Snowflake, DBT (Data Build Tool), and SAP Data Services (SAP DS). The ideal candidate will be responsible for building scalable data pipelines, designing robust data models, and ensuring high data quality across enterprise platforms. Key Responsibilities: Design, build, and optimize data pipelines and ETL/ELT workflows using Snowflake and DBT Integrate and manage data from various sources using SAP Data Services Develop and maintain scalable data models, data marts, and data warehouses Work closely with data analysts, business stakeholders, and BI teams to support reporting and analytics needs Implement best practices in data governance, data lineage, and metadata management Monitor data quality, troubleshoot issues, and ensure data integrity Optimize Snowflake data warehouse performance (partitioning, caching, query tuning) Automate data workflows and deploy DBT models with CI/CD tools (e.g., Git, Jenkins) Document architecture, data flows, and technical specifications

Job Summary: We are looking for a highly skilled Senior Data Engineer with expertise in Snowflake, DBT (Data Build Tool), and SAP Data Services (SAP DS). The ideal candidate will be responsible for building scalable data pipelines, designing robust data models, and ensuring high data quality across enterprise platforms. Key Responsibilities: Design, build, and optimize data pipelines and ETL/ELT workflows using Snowflake and DBT Integrate and manage data from various sources using SAP Data Services Develop and maintain scalable data models, data marts, and data warehouses Work closely with data analysts, business stakeholders, and BI teams to support reporting and analytics needs Implement best practices in data governance, data lineage, and metadata management Monitor data quality, troubleshoot issues, and ensure data integrity Optimize Snowflake data warehouse performance (partitioning, caching, query tuning) Automate data workflows and deploy DBT models with CI/CD tools (e.g., Git, Jenkins) Document architecture, data flows, and technical specifications

Job Summary: We are looking for a results-driven Sales Executive to actively seek out and engage customer prospects. You will provide complete and appropriate solutions for every customer in order to boost top-line revenue growth, customer acquisition levels, and profitability. Key Responsibilities: Identify and approach potential customers through cold calls, emails, and in-person meetings Understand customer needs and recommend suitable products/services Achieve monthly and quarterly sales targets Build and maintain strong, long-lasting customer relationships Prepare and deliver sales presentations and proposals Maintain records of all sales leads and customer accounts Collaborate with team members to achieve better results Provide post-sales support and ensure customer satisfaction

Job Summary: We are looking for a results-driven Sales Executive to actively seek out and engage customer prospects. You will provide complete and appropriate solutions for every customer in order to boost top-line revenue growth, customer acquisition levels, and profitability. Key Responsibilities: Identify and approach potential customers through cold calls, emails, and in-person meetings Understand customer needs and recommend suitable products/services Achieve monthly and quarterly sales targets Build and maintain strong, long-lasting customer relationships Prepare and deliver sales presentations and proposals Maintain records of all sales leads and customer accounts Collaborate with team members to achieve better results Provide post-sales support and ensure customer satisfaction

Required Skills 5 - 8 years of experience with Informatica Cloud (IDMC), including: Mappings, tasks, Taskflows, Parameterization Strong PLSQL/SQL Server development experience Experience working with flat file ingestion, header validation, and data sanitization. Strong understanding of ETL best practices, error handling, logging, and performance tuning. Experience with Snowflake, OCI, or other modern cloud data platforms. Knowledge of CI/CD for IDMC (e.g., Git integration, deployment groups). Familiarity with cloud storage (e.g., AWS S3, Azure Blob, OCI object storage) and API integration. Basic scripting skills (e.g., Bash, Python) for automation tasks. Informatica certifications (e.g., IDMC Cloud Data Integration Specialist) are a plus. Key Responsibilities Design, develop, and optimize ETL mappings, taskflows in Informatica IDMC Translate transformation logic from business requirements into scalable ETL jobs Collaborate with offshore testing team to resolve defects and ensure test coverage Implement parameterized, reusable, and modular pipelines aligned with naming and coding standards Work with offshore control M and DBAs to setup job in lower environments Work in agile environment, delivering prioritized work within expected timelines Troubleshoot and debug QA issues independently Email : Mayank@axiomsoftwaresolutions.com Phone : 9584022831

Job Summary: We are looking for a highly skilled Senior Data Engineer with expertise in Snowflake, DBT (Data Build Tool), and SAP Data Services (SAP DS). The ideal candidate will be responsible for building scalable data pipelines, designing robust data models, and ensuring high data quality across enterprise platforms. Key Responsibilities: Design, build, and optimize data pipelines and ETL/ELT workflows using Snowflake and DBT Integrate and manage data from various sources using SAP Data Services Develop and maintain scalable data models, data marts, and data warehouses Work closely with data analysts, business stakeholders, and BI teams to support reporting and analytics needs Implement best practices in data governance, data lineage, and metadata management Monitor data quality, troubleshoot issues, and ensure data integrity Optimize Snowflake data warehouse performance (partitioning, caching, query tuning) Automate data workflows and deploy DBT models with CI/CD tools (e.g., Git, Jenkins) Document architecture, data flows, and technical specifications

Job Summary: We are looking for a highly skilled Senior Data Engineer with expertise in Snowflake, DBT (Data Build Tool), and SAP Data Services (SAP DS). The ideal candidate will be responsible for building scalable data pipelines, designing robust data models, and ensuring high data quality across enterprise platforms. Key Responsibilities: Design, build, and optimize data pipelines and ETL/ELT workflows using Snowflake and DBT Integrate and manage data from various sources using SAP Data Services Develop and maintain scalable data models, data marts, and data warehouses Work closely with data analysts, business stakeholders, and BI teams to support reporting and analytics needs Implement best practices in data governance, data lineage, and metadata management Monitor data quality, troubleshoot issues, and ensure data integrity Optimize Snowflake data warehouse performance (partitioning, caching, query tuning) Automate data workflows and deploy DBT models with CI/CD tools (e.g., Git, Jenkins) Document architecture, data flows, and technical specifications

Role: Azure Specialist-DBT Location: Bangalore Mode: Remote Education and Work Experience Requirements: •Overall, 5 to 9 years of experience in IT Industry. Min 6 years of experience working on Data Engineering. Translate complex business requirements into analytical SQL views using DBT Support data ingestion pipelines using Airflow and Data Factory Develop DBT macros to enable scalable and reusable code automation Mandatory Skills: Strong experience with DBT (Data Build Tool)( (or strong SQL / relational DWH knowledge)-Must have Proficiency in SQL and strong understanding of relational data warehouse concept Hands-on experience with Databricks (primarily Databricks SQL) good to have Familiarity with Apache Airflow and Azure Data Factory – nice to have Experience working with Snowflake – nice to have Additional Information: Qualifications - BE, MS, M.Tech or MCA. Certifications: Azure Big Data, Databricks Certified Associate

Key Responsibilities: Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience : 5-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e.g., source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e.g., trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams. Mandatory Competencies QA/QE - QA Automation - ETL Testing ETL - ETL - Tester Beh - Communication and collaboration Database - Sql Server - SQL Packages Database - PostgreSQL - PostgreSQL

Role Description : As a Technical Lead - Datawarehousing Development at Incedo, you will be responsible for designing and developing data warehousing solutions. You should have experience with ETL tools such as Informatica, Talend, or DataStage and be proficient in SQL. Roles & Responsibilities: Design and develop data warehousing solutions using tools like Hadoop, Spark, or Snowflake Write efficient and optimized ETL scripts Collaborate with cross-functional teams to develop and implement data warehousing features and enhancements Debug and troubleshoot complex data warehousing issues Ensure data security, availability, and scalability of production systems Technical Skills Skills Requirements: Proficiency in ETL (Extract, Transform, Load) processes and tools such as Informatica, Talend, or DataStage. Experience with data modeling and schema design for data warehousing applications. Knowledge of data warehouse technologies such as Amazon Redshift, Snowflake, or Oracle Exadata. Familiarity with business intelligence (BI) tools such as Tableau, Power BI, or QlikView. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred .

Job Description At NAVEX, were making the world a better place. A safer place. A more ethical place. A place where anyone, anywhere can have a voice. Thats a serious impact. You will join our Product Engineering team that shares a passion for writing great code, embracing new technologies and delivering powerful products within our integrated risk and compliance management platform that helps our customers protect their reputation and bottom line. As a Data Senior Staff Software Engineer, you will influence technical designs and implement our new data platform. You will focus on quality implementation while guiding the other data engineers. You will help us build a data platform that will ingest other teams’ content and then provide application specific data sets. We are looking for a candidate who is strong in data engineering. In this role, you will have ample opportunity to explore new value-added capabilities, invest in data development and tool research, mentor software developers and grow your career all while balancing your life priorities. What you’ll get: Career growth. With market-leading training and an unwavering commitment to owning your career plan, you can grow your career to new heights. Real rewards. We offer competitive and transparent pay practices, top-of-the-range wellbeing programs, and brilliant opt-in benefits. Because we believe companies should offer more than just a salary. Meaningful purpose. Our products and solutions have real-life impact on people and organizations across the globe. Our innovations make a difference. Life flexibility. We want you to bring your best self to work every day. We understand that you can only do that with quality time to care for yourself, your loved ones and your community. An inspiring culture. Find yourself surrounded by leaders that care, invested teammates, and like-minded groups where you’ll feel at home. Industry leadership. Play your part in a fast-growing organization known for excellence, profitability, and stability. What you’ll do: Work with a team of data engineers and be accountable for designs and high-quality deliveries as an individual contributor Help team members grow by mentoring newer engineers Participate in the innovative advancements of our product platform and collaborate with our awesome agile team members Promote opportunities for refactoring and identify areas of optimization Research and leverage commercial products, libraries, and tools that can be used to solve problems Participate in design sessions with other engineers, architects, and product managers, providing constructive and honest feedback during sprint retrospectives with a team mindset Use automation, including continuous integration, automated deployments, and automated unit and functional testing What you’ll need: 8+ years of experience in software development, with more than 6 years of specialized expertise in data engineering Expert knowledge of data management and pipeline systems, practices, and standards Expert analytical and design skills, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems Expertise in the fields of data transformations (ELT, ETL), data quality, data cleansing, and data profiling using dbt Labs’ DBT Expertise in Data Cataloging and Master Data Management concepts Expertise in both SQL and NoSQL implementations; experience with Microsoft SQL Server, Snowflake, and Postgres database platforms Experience with SQL profiling, performance tuning, and data ingestion into Data Warehouses Strong critical thinking skills with the ability to identify and influence others on the best solution Ability to drive results through your job competencies of collaboration, software programming and development, and technical problem solving Ability to drive results through NAVEX core competencies of accountability, customer focus, drives results and instills trust Our side of the deal: We believe everyone deserves to see their path forward, and the steps in place to achieve their career and financial goals. Every team member is required to have a career plan in place, to be reviewed with their manager after six months in our team. The starting pay rate for this role is 2,829,000 INR with a 5% MBO. Pay progression based on your performance. We’re committed to helping you thrive in all aspects of your life. Our pay programs are just one element of this. Check out NAVEX’s career page to find out more information. We’re an equal opportunity employer, including all disability and veteran status. ole & responsibilities Preferred candidate profile

Lead Software Engineer Backend Were seeking a Lead Software Engineer to join one of our Data Layer teams. As the name implies, the Data Layer is at the core of all things data at Zeta. Our responsibilities include: Developing and maintaining the Zeta Identity Graph platform, which collects billions of behavioural, demographic, environmental, and transactional signals to power people-based marketing. Ingesting vast amounts of identity and event data from our customers and partners. Facilitating data transfers across systems. Ensuring the integrity and health of our datasets. And much more. As a member of this team, the data engineer will be responsible for designing and expanding our existing data infrastructure, enabling easy access to data, supporting complex data analyses, and automating optimization workflows for business and marketing operations. Essential Responsibilities: As a Lead Software Engineer, your responsibilities will include: Building, refining, tuning, and maintaining our real-time and batch data infrastructure Daily use technologies such as Python, Spark, Airflow, Snowflake, Hive, Scylla, Django, FastAPI, etc. Maintaining data quality and accuracy across production data systems Working with Data Engineers to optimize data models and workflows Working with Data Analysts to develop ETL processes for analysis and reporting Working with Product Managers to design and build data products Working with our DevOps team to scale and optimize our data infrastructure Participate in architecture discussions, influence the road map, take ownership and responsibility over new projects Participating in on-call rotation in their respective time zones (be available by phone or email in case something goes wrong) Desired Characteristics: Minimum 5 years of software engineering experience. Proven long term experience and enthusiasm for distributed data processing at scale, eagerness to learn new things. Expertise in designing and architecting distributed low latency and scalable solutions in either cloud and onpremises environment. Exposure to the whole software development lifecycle from inception to production and monitoring Fluency in Python or solid experience in Scala, Java Proficient with relational databases and Advanced SQL Expert in usage of services like Spark and Hive Experience with web frameworks such as Flask, Djang Experience in adequate usage of any scheduler such as Apache Airflow, Apache Luigi, Chronos etc. Experience in adequate usage of cloud services (AWS) at scale Experience in agile software development processes Excellent interpersonal and communication skills Nice to have: Experience with large scale / multi-tenant distributed systems Experience with columnar / NoSQL databases Vertica, Snowflake, HBase, Scylla, Couchbase Experience in real team streaming frameworks Flink, Storm Experience in open table formats such as Iceberg, Hudi or Deltalake

As a member of this team, the data engineer will be responsible for designing and expanding our existing data infrastructure, enabling easy access to data, supporting complex data analyses, and automating optimization workflows for business and marketing operations Essential Responsibilities: As a Senior Software Engineer, your responsibilities will include: Building, refining, tuning, and maintaining our real-time and batch data infrastructure Daily use technologies such as Python, Spark, Airflow, Snowflake, Hive, FastAPI, etc. Maintaining data quality and accuracy across production data systems Working with Data Analysts to develop ETL processes for analysis and reporting Working with Product Managers to design and build data products Working with our DevOps team to scale and optimize our data infrastructure Participate in architecture discussions, influence the road map, take ownership and responsibility over new projects Participating in on-call rotation in their respective time zones (be available by phone or email in case something goes wrong) Desired Characteristics: Minimum 8 years of software engineering experience. An undergraduate degree in Computer Science (or a related field) from a university where the primary language of instruction is English is strongly desired. 2+ Years of Experience/Fluency in Python Proficient with relational databases and Advanced SQL Expert in usage of services like Spark and Hive. Experience working with container-based solutions is a plus. Experience in adequate usage of any scheduler such as Apache Airflow, Apache Luigi, Chronos etc. Experience in adequate usage of cloud services (AWS) at scale Proven long term experience and enthusiasm for distributed data processing at scale, eagerness to learn new things. Expertise in designing and architecting distributed low latency and scalable solutions in either cloud and on-premises environment. Exposure to the whole software development lifecycle from inception to production and monitoring. Experience in Advertising Attribution domain is a plus Experience in agile software development processes Excellent interpersonal and communication skills

CDP ETL & Database Engineer The CDP ETL & Database Engineer will specialize in architecting, designing, and implementing solutions that are sustainable and scalable. The ideal candidate will understand CRM methodologies, with an analytical mindset, and a background in relational modeling in a Hybrid architecture. The candidate will help drive the business towards specific technical initiatives and will work closely with the Solutions Management, Delivery, and Product Engineering teams. The candidate will join a team of developers across the US, India & Costa Rica. Responsibilities : ETL Development The CDP ETL & Database Engineer will be responsible for building pipelines to feed downstream data processes. They will be able to analyze data, interpret business requirements, and establish relationships between data sets. The ideal candidate will be familiar with different encoding formats and file layouts such as JSON and XML. I mplementations & Onboarding Will work with the team to onboard new clients onto the ZMP/CDP+ platform. The candidate will solidify business requirements, perform ETL file validation, establish users, perform complex aggregations, and syndicate data across platforms. The hands-on engineer will take a test-driven approach towards development and will be able to document processes and workflows. Incremental Change Requests The CDP ETL & Database Engineer will be responsible for analyzing change requests and determining the best approach towards implementation and execution of the request. This requires the engineer to have a deep understanding of the platform's overall architecture. Change requests will be implemented and tested in a development environment to ensure their introduction will not negatively impact downstream processes. Change Data Management The candidate will adhere to change data management procedures and actively participate in CAB meetings where change requests will be presented and approved. Prior to introducing change, the engineer will ensure that processes are running in a development environment. The engineer will be asked to do peer-to-peer code reviews and solution reviews before production code deployment. Collaboration & Process Improvement The engineer will be asked to participate in knowledge share sessions where they will engage with peers, discuss solutions, best practices, overall approach, and process. The candidate will be able to look for opportunities to streamline processes with an eye towards building a repeatable model to reduce implementation duration. Job Requirements : The CDP ETL & Database Engineer will be well versed in the following areas: Relational data modeling ETL and FTP concepts Advanced Analytics using SQL Functions Cloud technologies - AWS, Snowflake Able to decipher requirements, provide recommendations, and implement solutions within predefined timeframes. The ability to work independently, but at the same time, the individual will be called upon to contribute in a team setting. The engineer will be able to confidently communicate status, raise exceptions, and voice concerns to their direct manager. Participate in internal client project status meetings with the Solution/Delivery management teams. When required, collaborate with the Business Solutions Analyst (BSA) to solidify requirements. Ability to work in a fast paced, agile environment; the individual will be able to work with a sense of urgency when escalated issues arise. Strong communication and interpersonal skills, ability to multitask and prioritize workload based on client demand. Familiarity with Jira for workflow mgmt., and time allocation. Familiarity with Scrum framework, backlog, planning, sprints, story points, retrospectives etc. Required Skills : ETL ETL tools such as Talend (Preferred, not required) DMExpress Nice to have Informatica Nice to have Database - Hands on experience with the following database Technologies Snowflake (Required) MYSQL/PostgreSQL Nice to have Familiar with NOSQL DB methodologies (Nice to have) Programming Languages Can demonstrate knowledge of any of the following. PLSQL JavaScript Strong Plus Python - Strong Plus Scala - Nice to have AWS Knowledge of the following AWS services: S3 EMR (Concepts) EC2 (Concepts) Systems Manager / Parameter Store Understands JSON Data structures, key value pair. Working knowledge of Code Repositories such as GIT, Win CVS, SVN. Workflow management tools such as Apache Airflow, Kafka, Automic/Appworx Jira Minimum Qualifications Bachelor's degree or equivalent 2-4 Years' experience Excellent verbal & written communications skills Self-Starter, highly motivated Analytical mindset.

3+ years of experience as a Snowflake Developer or Data Engineer. Strong knowledge of SQL, SnowSQL, and Snowflake schema design. Experience with ETL tools and data pipeline automation. Basic understanding of US healthcare data (claims, eligibility, providers, payers). Experience working with largescale datasets and cloud platforms (AWS, Azure,GCP). Familiarity with data governance, security, and compliance (HIPAA, HITECH).

Summary: We are seeking a highly skilled and experienced Snowflake Database Administrator (DBA) to join our team. The ideal candidate will be responsible for the administration, management, and optimization of our Snowflake data platform. The role requires strong expertise in database design, performance tuning, security, and data governance within the Snowflake environment. Key Responsibilities: Administer and manage Snowflake cloud data warehouse environments, including provisioning, configuration, monitoring, and maintenance. Implement security policies, compliance, and access controls. Manage Snowflake accounts and databases in a multi-tenant environment. Monitor the systems and provide proactive solutions to ensure high availability and reliability. Monitor and manage Snowflake costs. Collaborate with developers, support engineers and business stakeholders to ensure efficient data integration. Automate database management tasks and procedures to improve operational efficiency. Stay up to date with the latest Snowflake features, best practices, and industry trends to enhance the overall data architecture. Develop and maintain documentation, including database configurations, processes, and standard operating procedures. Support disaster recovery and business continuity planning for Snowflake environments. Required Qualifications: Bachelors degree in computer science, Information Technology, or a related field. 5+ years of experience in Snowflake operations and administration. Strong knowledge of SQL, query optimization, and performance tuning techniques. Experience in managing security, access controls, and data governance in Snowflake. Familiarity with AWS. Proficiency in Python or Bash. Experience in automating database tasks using Terraform, CloudFormation, or similar tools. Understanding of data modeling concepts and experience working with structured and semi-structured data (JSON, Avro, Parquet). Strong analytical, problem-solving, and troubleshooting skills. Excellent communication and collaboration abilities. Preferred Qualifications: Snowflake certification (e.g., SnowPro Core, SnowPro Advanced: Architect, Administrator). Experience with CI/CD pipelines and DevOps practices for database management. Knowledge of machine learning and analytics workflows within Snowflake. Hands-on experience with data streaming technologies (Kafka, AWS Kinesis, etc.).

Roles and Responsibilities : Design, develop, test, deploy and maintain large-scale data pipelines using PySpark on Microsoft Azure platform. Collaborate with cross-functional teams to gather requirements and deliver high-quality data solutions that meet business needs. Develop complex SQL queries to extract insights from Snowflake databases and integrate them into the pipeline. Troubleshoot issues related to data processing, storage, and retrieval in real-time. Job Requirements : 4-12 years of experience in designing and developing big data architectures on cloud platforms like Microsoft Azure. Strong expertise in working with PySpark for building scalable data pipelines. Proficiency in writing complex SQL queries for querying large datasets stored in Snowflake databases.