18 Spark Sql Jobs

Please Note - NP should be 0-15 days Looking for 10+ Y / highly experienced and deeply hands-on Data Architect to lead the design, build, and optimization of our data platforms on AWS and Databricks. This role requires a strong blend of architectural vision and direct implementation expertise, ensuring scalable, secure, and performant data solutions from concept to production. Strong hand on exp in data engineering/architecture, hands-on architectural and implementation experience on AWS and Databricks, Schema modeling . AWS: Deep hands-on expertise with key AWS data services and infrastructure. Databricks: Expert-level hands-on development with Databricks (Spark SQL, PySpark), Delta Lake, and Unity Catalog. Coding: Exceptional proficiency in Python , Pyspark , Spark , AWS Services and SQL. Architectural: Strong data modeling and architectural design skills with a focus on practical implementation. Preferred: AWS/Databricks certifications, experience with streaming technologies, and other data tools. Design & Build: Lead and personally execute the design, development, and deployment of complex data architectures and pipelines on AWS (S3, Glue, Lambda, Redshift, etc.) and Databricks (PySpark/Spark SQL, Delta Lake, Unity Catalog). Databricks Expertise: Own the hands-on development, optimization, and performance tuning of Databricks jobs, clusters, and notebooks.

The Data Scientist-3 in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk, Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are deployed for real time or near real time consumption and integrated into our proprietary Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the growth trajectory of a super fast evolving digital product. Key Requirements of The Role Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 7 - 10 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product and business teams Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets. Strong experience in NLP, time series forecasting and recommendation engines preferred Create great data stories with expertise in robust EDA and statistical inference. Should have at least a foundational understanding in Experimentation design ? Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch, Caffe preferred Experience with analytical programming languages, tools and libraries (Python a must) as well as Shell scripting. Should be proficient in developing production ready code as per best practices. Experience in using Scala/Java/Go based libraries a big plus Very proficient is SQL and other relational databases along with PySpark or Spark SQL. Proficient is using NoSQL databases. Experience in using GraphDBs like Neo4j a plus. Candidate should be able to handle unstructured data with ease. Candidate should have experience in working with MLEs and be proficient (with experience) in using MLOps tools. Should be able to consume the capabilities of said tools with deep understanding of deployment lifecycle. Experience in CI/CD deployment is a big plus. Knowledge of key concepts in distributed systems like replication, serialization, concurrency control etc. a big plus Good understanding of programming best practices and building code artifacts for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git Ability to create frameworks that can perform model RCAs using analytical and interpretability tools. Should be able to peer review model documentations/code bases and find opportunities Experience in end-to-end delivery of AI driven Solutions (Deep learning , traditional data science projects) Strong communication, partnership and teamwork skills ? Should be able to guide and mentor teams while leading them by example. Should be an integral part of creating a team culture focused on driving collaboration, technical expertise and partnerships with other teams ? Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision A self-starter who is looking to build grounds up and contribute to the making of a potential big name in the space ? Experience in Banking and financial services is a plus. However, sound logical reasoning and first principles problem solving are even more critical job role: 1. As a key partner at the table, attend key meetings with the business team to bring in the data perspective to the discussions 2. Perform comprehensive data explorations around to generate inquisitive insights and scope out the problem 3. Develop simplistic to advanced solutions to address the problem at hand. We believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development 4. Build re-usable code analytical frameworks to address commonly occurring business questions 5. Perform 360-degree customer profiling and opportunity analyses to guide new product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty 6. Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges 7. The role will be an approximate 60% IC 40% leading and the ratios can vary basis need and fit 8. Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer

Job Description: We are looking for energetic, self-motivated and exceptional Data engineer to work on extraordinary enterprise products based on AI and Big Data engineering leveraging AWS/Databricks tech stack. He/she will work with star team of Architects, Data Scientists/AI Specialists, Data Engineers and Integration. Skills and Qualifications: 5+ years of experience in DWH/ETL Domain; Databricks/AWS tech stack 2+ years of experience in building data pipelines with Databricks/ PySpark /SQL Experience in writing and interpreting SQL queries, designing data models and data standards. Experience in SQL Server databases, Oracle and/or cloud databases. Experience in data warehousing and data mart, Star and Snowflake model. Experience in loading data into database from databases and files. Experience in analyzing and drawing design conclusions from data profiling results. Understanding business process and relationship of systems and applications. Must be comfortable conversing with the end-users. Must have ability to manage multiple projects/clients simultaneously. Excellent analytical, verbal and communication skills. Role and Responsibilities: Work with business stakeholders and build data solutions to address analytical & reporting requirements. Work with application developers and business analysts to implement and optimise Databricks/AWS-based implementations meeting data requirements. Design, develop, and optimize data pipelines using Databricks (Delta Lake, Spark SQL, PySpark), AWS Glue, and Apache Airflow Implement and manage ETL workflows using Databricks notebooks, PySpark and AWS Glue for efficient data transformation Develop/ optimize SQL scripts, queries, views, and stored procedures to enhance data models and improve query performance on managed databases. Conduct root cause analysis and resolve production problems and data issues. Create and maintain up to date documentation of the data model, data flow and field level mappings. Provide support for production problems and daily batch processing. Provide ongoing maintenance and optimization of database schemas, data lake structures (Delta Tables, Parquet), and views to ensure data integrity and performance

We are looking for energetic, self-motivated and exceptional Data engineer to work on extraordinary enterprise products based on AI and Big Data engineering leveraging AWS/Databricks tech stack. He/she will work with star team of Architects, Data Scientists/AI Specialists, Data Engineers and Integration. Skills and Qualifications: 5+ years of experience in DWH/ETL Domain; Databricks/AWS tech stack 2+ years of experience in building data pipelines with Databricks/ PySpark /SQL Experience in writing and interpreting SQL queries, designing data models and data standards. Experience in SQL Server databases, Oracle and/or cloud databases. Experience in data warehousing and data mart, Star and Snowflake model. Experience in loading data into database from databases and files. Experience in analyzing and drawing design conclusions from data profiling results. Understanding business process and relationship of systems and applications. Must be comfortable conversing with the end-users. Must have ability to manage multiple projects/clients simultaneously. Excellent analytical, verbal and communication skills. Role and Responsibilities: Work with business stakeholders and build data solutions to address analytical & reporting requirements. Work with application developers and business analysts to implement and optimise Databricks/AWS-based implementations meeting data requirements. Design, develop, and optimize data pipelines using Databricks (Delta Lake, Spark SQL, PySpark), AWS Glue, and Apache Airflow Implement and manage ETL workflows using Databricks notebooks, PySpark and AWS Glue for efficient data transformation Develop/ optimize SQL scripts, queries, views, and stored procedures to enhance data models and improve query performance on managed databases. Conduct root cause analysis and resolve production problems and data issues. Create and maintain up to date documentation of the data model, data flow and field level mappings. Provide support for production problems and daily batch processing. Provide ongoing maintenance and optimization of database schemas, data lake structures (Delta Tables, Parquet), and views to ensure data integrity and performance

About the Roe: Grade Leve (for interna use): 11 The Team: Our team is responsibe for the design, architecture, and deveopment of our cient facing appications using a variety of toos that are reguary updated as new technoogies emerge. You wi have the opportunity every day to work with peope from a wide variety of backgrounds and wi be abe to deveop a cose team dynamic with coworkers from around the gobe. The Impact: The work you do wi be used every singe day, its the essentia code you write that provides the data and anaytics required for crucia, daiy decisions in the capita and commodities markets. Whats in it for you: Buid a career with a goba company. Work on code that fues the goba financia markets. Grow and improve your skis by working on enterprise eve products and new technoogies. Responsibiities: Sove probems, anayze and isoate issues.Provide technica guidance and mentoring to the team and hep them adopt change as new processes are introduced.Champion best practices and serve as a subject matter authority.Deveop soutions to deveop/support key business needs.Engineer components and common services based on standard deveopment modes, anguages and toosProduce system design documents and ead technica wakthroughsProduce high quaity codeCoaborate effectivey with technica and non-technica partnersAs a team-member shoud continuousy improve the architecture Basic Quaifications: 10-12 years of experience designing/buiding data-intensive soutions using distributed computing.Proven experience in impementing and maintaining enterprise search soutions in arge-scae environments.Experience working with business stakehoders and users, providing research direction and soution design and writing robust maintainabe architectures and APIs.Experience deveoping and depoying Search soutions in a pubic coud such as AWS.Proficient programming skis at a high-eve anguages -Java, Scaa, PythonSoid knowedge of at east one machine earning research frameworksFamiiarity with containerization, scripting, coud patforms, and CI/CD.5+ years experience with Python, Java, Kubernetes, and data and workfow orchestration toos4+ years experience with Easticsearch, SQL, NoSQL,Apache spark, Fink, Databricks and Mfow.Prior experience with operationaizing data-driven pipeines for arge scae batch and stream processing anaytics soutionsGood to have experience with contributing to GitHub and open source initiatives or in research projects and/or participation in Kagge competitionsAbiity to quicky, efficienty, and effectivey define and prototype soutions with continua iteration within aggressive product deadines.Demonstrate strong communication and documentation skis for both technica and non-technica audiences. Preferred Quaifications: Search TechnoogiesQuery and Indexing content for Apache Sor, Eastic Search, etc.Proficiency in search query anguages (e.g., Lucene Query Syntax) and experience with data indexing and retrieva.Experience with machine earning modes and NLP techniques for search reevance and ranking.Famiiarity with vector search techniques and embedding modes (e.g., BERT, Word2Vec).Experience with reevance tuning using A/B testing frameworks.Big Data TechnoogiesApache Spark, Spark SQL, Hadoop, Hive, AirfowData Science Search TechnoogiesPersonaization and Recommendation modes, Learn to Rank (LTR)Preferred LanguagesPython, JavaDatabase TechnoogiesMS SQL Server patform, stored procedure programming experience using Transact SQL.Abiity to ead, train and mentor. About S&P Goba Market Inteigence At S&P Goba Market Inteigence, a division of S&P Goba we understand the importance of accurate, deep and insightfu information. Our team of experts deivers unrivaed insights and eading data and technoogy soutions, partnering with customers to expand their perspective, operate with confidence, andmake decisions with conviction.For more information, visit . Whats In It For You Our Purpose: Progress is not a sef-starter. It requires a catayst to be set in motion. Information, imagination, peope, technoogythe right combination can unock possibiity and change the word.Our word is in transition and getting more compex by the day. We push past expected observations and seek out new eves of understanding so that we can hep companies, governments and individuas make an impact on tomorrow. At S&P Goba we transform data into Essentia Inteigence, pinpointing risks and opening possibiities. We Acceerate Progress.

Job Summary Synechron is seeking an experienced and technically proficient Senior PySpark Data Engineer to join our data engineering team. In this role, you will be responsible for developing, optimizing, and maintaining large-scale data processing solutions using PySpark. Your expertise will support our organizations efforts to leverage big data for actionable insights, enabling data-driven decision-making and strategic initiatives. Software Requirements Required Skills: Proficiency in PySpark Familiarity with Hadoop ecosystem components (e.g., HDFS, Hive, Spark SQL) Experience with Linux/Unix operating systems Data processing tools like Apache Kafka or similar streaming platforms Preferred Skills: Experience with cloud-based big data platforms (e.g., AWS EMR, Azure HDInsight) Knowledge of Python (beyond PySpark), Java or Scala relevant to big data applications Familiarity with data orchestration tools (e.g., Apache Airflow, Luigi) Overall Responsibilities Design, develop, and optimize scalable data processing pipelines using PySpark. Collaborate with data engineers, data scientists, and business analysts to understand data requirements and deliver solutions. Implement data transformations, aggregations, and extraction processes to support analytics and reporting. Manage large datasets in distributed storage systems, ensuring data integrity, security, and performance. Troubleshoot and resolve performance issues within big data workflows. Document data processes, architectures, and best practices to promote consistency and knowledge sharing. Support data migration and integration efforts across varied platforms. Strategic Objectives: Enable efficient and reliable data processing to meet organizational analytics and reporting needs. Maintain high standards of data security, compliance, and operational durability. Drive continuous improvement in data workflows and infrastructure. Performance Outcomes & Expectations: Efficient processing of large-scale data workloads with minimum downtime. Clear, maintainable, and well-documented code. Active participation in team reviews, knowledge transfer, and innovation initiatives. Technical Skills (By Category) Programming Languages: Required: PySpark (essential); Python (needed for scripting and automation) Preferred: Java, Scala Databases/Data Management: Required: Experience with distributed data storage (HDFS, S3, or similar) and data warehousing solutions (Hive, Snowflake) Preferred: Experience with NoSQL databases (Cassandra, HBase) Cloud Technologies: Required: Familiarity with deploying and managing big data solutions on cloud platforms such as AWS (EMR), Azure, or GCP Preferred: Cloud certifications Frameworks and Libraries: Required: Spark SQL, Spark MLlib (basic familiarity) Preferred: Integration with streaming platforms (e.g., Kafka), data validation tools Development Tools and Methodologies: Required: Version control systems (e.g., Git), Agile/Scrum methodologies Preferred: CI/CD pipelines, containerization (Docker, Kubernetes) Security Protocols: Optional: Basic understanding of data security practices and compliance standards relevant to big data management Experience Requirements Minimum of 7+ years of experience in big data environments with hands-on PySpark development. Proven ability to design and implement large-scale data pipelines. Experience working with cloud and on-premises big data architectures. Preference for candidates with domain-specific experience in finance, banking, or related sectors. Candidates with substantial related experience and strong technical skills in big data, even from different domains, are encouraged to apply. Day-to-Day Activities Develop, test, and deploy PySpark data processing jobs to meet project specifications. Collaborate in multi-disciplinary teams during sprint planning, stand-ups, and code reviews. Optimize existing data pipelines for performance and scalability. Monitor data workflows, troubleshoot issues, and implement fixes. Engage with stakeholders to gather new data requirements, ensuring solutions are aligned with business needs. Contribute to documentation, standards, and best practices for data engineering processes. Support the onboarding of new data sources, including integration and validation. Decision-Making Authority & Responsibilities: Identify performance bottlenecks and propose effective solutions. Decide on appropriate data processing approaches based on project requirements. Escalate issues that impact project timelines or data integrity. Qualifications Bachelors degree in Computer Science, Information Technology, or related field. Equivalent experience considered. Relevant certifications are preferred: Cloudera, Databricks, AWS Certified Data Analytics, or similar. Commitment to ongoing professional development in data engineering and big data technologies. Demonstrated ability to adapt to evolving data tools and frameworks. Professional Competencies Strong analytical and problem-solving skills, with the ability to model complex data workflows. Excellent communication skills to articulate technical solutions to non-technical stakeholders. Effective teamwork and collaboration in a multidisciplinary environment. Adaptability to new technologies and emerging trends in big data. Ability to prioritize tasks effectively and manage time in fast-paced projects. Innovation mindset, actively seeking ways to improve data infrastructure and processes.

Databricks developer with deep SQL expertise to support the development of scalable data pipelines and analytics workflows, will work closely with data engineers BIanalysts to prepare clean, query-optimized datasets for reporting and modeling.

About the Role: We are seeking a skilled and experienced Data Engineer to join our remote team. The ideal candidate will have 5-7 years of professional experience working with Python, PySpark, SQL, and Spark SQL, and will play a key role in building scalable data pipelines, optimizing data workflows, and supporting data-driven decision-making across the organization. Key Responsibilities: Design, build, and maintain scalable and efficient data pipelines using PySpark and SQL. Develop and optimize Spark jobs for large-scale data processing. Collaborate with data scientists, analysts, and other engineers to ensure data quality and accessibility. Implement data integration from multiple sources into a unified data warehouse or lake. Monitor and troubleshoot data pipelines and ETL jobs for performance and reliability. Ensure best practices in data governance, security, and compliance. Create and maintain technical documentation related to data pipelines and infrastructure. Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad,Remote

Role Purpose The role incumbent is focused on implementation of roadmaps for business process analysis, data analysis, diagnosis of gaps, business requirements & functional definitions, best practices application, meeting facilitation, and contributes to project planning. Consultants are expected to contribute to solution building for the client & practice. The role holder can handle higher scale and complexity compared to a Consultant profile and is more proactive in client interactions. Do Assumes responsibilities as the main client contact leading engagement w/ 10-20% support from Consulting & Client Partners. Develops, assesses, and validates a clients business strategy, including industry and competitive positioning and strategic direction Develops solutions and services to suit clients business strategy Estimates scope and liability for delivery of the end product/solution Seeks opportunities to develop revenue in existing and new areas Leads an engagement and oversees others contributions at a customer end, such that customer expectations are met or exceeded. Drives Proposal creation and presales activities for the engagement; new accounts Contributes towards the development of practice policies, procedures, frameworks etc. Guides less experienced team members in delivering solutions. Leads efforts towards building go-to-market/ off the shelf / point solutions and process smethodologies for reuse Creates reusable IP from managed projects B?usiness System Analyst Skills required: Data warehousing, data analysis, ETL, SQL, spark SQL, data mapping, Azure, Databricks Pyspark and data bricks Experience in AML/ Banking/ Capital Market Experience with Agile methodology Plan, develop, test and deploy Experience with SQL server management tools and writing queries, with large SQL data marts, relational database experience. Profile data and prepare source to target mappings, map source data to the target tables for the multi hop architecture. Closely working with data modelers, data engineers and architect and product owners to identify any discrepancies and get it resolved. Strong knowledge of data extraction, design, load, and reporting solutions, strong ability to read SQL server SSIS packages, SQL stored procedures/functions and back trace views Work in the team of data designer/ developer to translate user and/or systems requirements into functional technical specifications. Work with business stakeholders and other SMEs to assess current capabilities, understand high-level business requirements and apply technical background/understanding in the development of System Requirements Specification (SRS) documents. Collaborate closely with Application Owners, Application Managers, and Solution Designers as the business/functional counterpart in solution identification and maintenance. Support testing teams in translating requirements and use cases into test conditions and expected results for product, performance, user acceptance, and operational acceptance testing; participate in the testing of developed systems/solutions. Act as a technical resource for business partners to ensure deliverables meet business and end-user requirements. Identifying the source data/source tables as per project specific use case and get that ingested into source raw zone. Raise Data access control requests and make source data available in analytical zone for data profiling and data analysis. Understanding the existing codes and data bricks workflows and leverage that for our use case. Mandatory Skills: Institutional Compliance. Experience: 8-10 Years.

Designation : Azure Data Engineer Experience : 5+ Years Location: Chennai, Bangalore, Pune, Mumbai Notice Period: Immediate Joiners/ Serving Notice Period Shift Timing: 3:30 PM IST to 12:30 AM IST Job Description : Azure Data Engineer: Must Have Azure Data Bricks, Azure Data Factory, Spark SQL with analytical knowledge Years 6-7 years of development experience in data engineering skills Strong experience in Spark. Understand complex data system by working closely with engineering and product teams Develop scalable and maintainable applications to extract, transform, and load data in various formats to SQL Server, Hadoop Data Lake or other data storage locations. Sincerely, Sonia HR Recruiter Talent Sketchers

Seeking an experienced Data Engineer who can play a crucial role in the company's fintech data lake project. Technical/Functional Skills: Must have 5+ years of experience working in data warehousing systems Strong experience in Oracle Fusion ecosystem, with strong data-extracting experience using Oracle BICC/BIP. Must have good functional understanding of Fusion data structures. Must have strong and proven data engineering experience in big data Databricks environment Must have hands-on experience building data ingestion pipelines from Oracle Fusion Cloud to a Databricks environment Strong data transformation/ETL skills using Spark SQL, Pyspark, Unity Catalog working in Databricks Medallion architecture Capable of independently delivering work items and leading data discussions with Tech Leads & Business Analysts Nice to have: Experience with Fivetran or any equivalent data extraction tools is nice to have. Experience in supporting Splash report development activities is a plus. Prefer experience with Git, CI/CD tools, and code management processes The candidate is expected to: Follow engineering best practices, coding standards, and deployment processes. Troubleshoot any performance, system or data related issues, and work to ensure data consistency and integrity. Effectively communicate with users at all levels of the organization, both in written and verbal presentations. Effectively communicate with other data engineers, help other team members with design and implementation activities. Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Design, Architect, and Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities. Develop POCs to influence platform architects, product managers and software engineers to validate solution proposals and migrate. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Build and optimize ETL workflows using Azure Databricks and PySpark. This includes developing efficient data processing pipelines, data validation, error handling, and performance tuning. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Articulates business requirements in a technical solution that can be designed and engineered. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 4 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them No Sql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams.

Role & responsibilities Urgent Hiring for one of the reputed MNC Exp - 5+ Years Location - Pan India Immediate Joiners only Snowflake developer , Pyspark , Python , API, CI/CD , Cloud services ,Azure , Azure Devops Subject: Fw : TMNA SNOWFLAKE POSITION Please share profiles for Snowflake developers having strong Pyspark experience Job Description: Strong hands-on experience in Snowflake development including Streams, Tasks, and Time Travel Deep understanding of Snowpark for Python and its application for data engineering workflows Proficient in PySpark , Spark SQL, and distributed data processing Experience with API development . Proficiency in cloud services (preferably Azure, but AWS/GCP also acceptable) Solid understanding of CI/CD practices and tools like Azure DevOps, GitHub Actions, GitLab, or Jenkins for snowflake. Knowledge of Delta Lake, Data Lakehouse principles, and schema evolution is a plus Preferred candidate profile

Role & responsibilities Urgent hiring for one of the reputed MNC Data Analyst Exp - 5 - 10 Years Only immediate joiners Location - Bangalore JD: Data Analyst Mandatory SKILLS 1. SQL : Proficient in database object creation including tables, views, indexes etc. Strong expertise in SQL queries ,Stored procedure & Function etc. Experienced in performance tuning & optimization techniques. 2.PowerBI : Proficiency in Power BI development, including report and dashboard creation Design, develop, and maintain complex Power BI data models, ensuring data integrity and consistency. Comprehensive understanding of data modeling and data visualization concepts Identify and resolve performance bottlenecks in Power BI reports and data models. Experience with Power Query & DAX 3. Problem-Solving Skills: Strong analytical and problem-solving skills to identify and resolve data-related issues. 4.Python : Strong proficiency in Python programming. 5.PySpark: Extensive experience with PySpark, including DataFrames & SparkSQL. Preferred candidate profile

Responsibilities: Solve problems, analyze and isolate issues. Provide technical guidance and mentoring to the team and help them adopt change as new processes are introduced. Champion best practices and serve as a subject matter authority. Develop solutions to develop/support key business needs. Engineer components and common services based on standard development models, languages and tools Produce system design documents and lead technical walkthroughs Produce high quality code Collaborate effectively with technical and non-technical partners As a team-member should continuously improve the architecture Basic Qualifications: 6-8 years of experience in application development using Java or Dot Net (.NET) Technologies Bachelor's /Masters degree in computer science, Information Systems or equivalent. Knowledge of object-oriented design, .NET framework and design patterns. Command of essential technologies: Java and/or C#, ASP.NET Experience with developing solutions involving relational database technologies: SQL, stored procedures Proficient with software development lifecycle (SDLC) methodologies like Agile, Test-Driven Development. Good communication and collaboration skills Preferred Qualifications: Search Technologies: Query and indexing content for Apache Solr, Elastic Search Big Data Technologies: Apache Spark, Spark SQL, Hadoop, Hive, Airflow Data Science Search Technologies: Personalization and Recommendation models, Learn to Rank (LTR) Preferred Languages: Python Database Technologies: MS SQL Server platform, stored procedure programming experience using Transact SQL. Ability to lead, train and mentor.

As the Full Stack Developer within the Data and Analytics team, you will be responsible for delivery of innovative data and analytics solutions, ensuring Al Futtaim Business stays at the forefront of technical development.

Role :- Resident Solution ArchitectLocation: RemoteThe Solution Architect at Koantek builds secure, highly scalable big data solutions to achieve tangible, data-driven outcomes all the while keeping simplicity and operational effectiveness in mind This role collaborates with teammates, product teams, and cross-functional project teams to lead the adoption and integration of the Databricks Lakehouse Platform into the enterprise ecosystem and AWS/Azure/GCP architecture This role is responsible for implementing securely architected big data solutions that are operationally reliable, performant, and deliver on strategic initiatives Specific requirements for the role include: Expert-level knowledge of data frameworks, data lakes and open-source projects such as Apache Spark, MLflow, and Delta Lake Expert-level hands-on coding experience in Python, SQL ,Spark/Scala,Python or Pyspark In depth understanding of Spark Architecture including Spark Core, Spark SQL, Data Frames, Spark Streaming, RDD caching, Spark MLib IoT/event-driven/microservices in the cloud- Experience with private and public cloud architectures, pros/cons, and migration considerations Extensive hands-on experience implementing data migration and data processing using AWS/Azure/GCP services Extensive hands-on experience with the Technology stack available in the industry for data management, data ingestion, capture, processing, and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc Experience using Azure DevOps and CI/CD as well as Agile tools and processes including Git, Jenkins, Jira, and Confluence Experience in creating tables, partitioning, bucketing, loading and aggregating data using Spark SQL/Scala Able to build ingestion to ADLS and enable BI layer for Analytics with strong understanding of Data Modeling and defining conceptual logical and physical data models Proficient level experience with architecture design, build and optimization of big data collection, ingestion, storage, processing, and visualization Responsibilities : Work closely with team members to lead and drive enterprise solutions, advising on key decision points on trade-offs, best practices, and risk mitigationGuide customers in transforming big data projects,including development and deployment of big data and AI applications Promote, emphasize, and leverage big data solutions to deploy performant systems that appropriately auto-scale, are highly available, fault-tolerant, self-monitoring, and serviceable Use a defense-in-depth approach in designing data solutions and AWS/Azure/GCP infrastructure Assist and advise data engineers in the preparation and delivery of raw data for prescriptive and predictive modeling Aid developers to identify, design, and implement process improvements with automation tools to optimizing data delivery Implement processes and systems to monitor data quality and security, ensuring production data is accurate and available for key stakeholders and the business processes that depend on it Employ change management best practices to ensure that data remains readily accessible to the business Implement reusable design templates and solutions to integrate, automate, and orchestrate cloud operational needs and experience with MDM using data governance solutions Qualifications : Overall experience of 12+ years in the IT field Hands-on experience designing and implementing multi-tenant solutions using Azure Databricks for data governance, data pipelines for near real-time data warehouse, and machine learning solutions Design and development experience with scalable and cost-effective Microsoft Azure/AWS/GCP data architecture and related solutions Experience in a software development, data engineering, or data analytics field using Python, Scala, Spark, Java, or equivalent technologies Bachelors or Masters degree in Big Data, Computer Science, Engineering, Mathematics, or similar area of study or equivalent work experience Good to have- - Advanced technical certifications: Azure Solutions Architect Expert, - AWS Certified Data Analytics, DASCA Big Data Engineering and Analytics - AWS Certified Cloud Practitioner, Solutions Architect - Professional Google Cloud Certified Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

Warm Greetings from SP Staffing!! Role: Pyspark Developer Experience Required :4 to 6 yrs Work Location: Hyderabad/Bangalore/Pune/Chennai/Kochi Required Skills, pyspark/python/spark sql/ETL Interested candidates can send resumes to nandhini.spstaffing@gmail.com