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Posted 1mo ago

Data Engineer (PySpark, Database, Python)

@ Virtusa
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Chennai, Tamil Nadu, India
OnsiteFull Time
Responsibilities:building pipelines, designing models, managing databases
Requirements Summary:Proficiency with PySpark, SQL and Python; hands-on ETL and data pipeline development; experience with big data platforms (Hadoop, Hive, Snowflake); relational and NoSQL database design; data modeling, CI/CD exposure and data governance.
Technical Tools Mentioned:PySpark, SQL, Python, Starburst, Ab Initio, Apache Spark, Talend, Hadoop, Hive, Snowflake, Oracle, MSSQL, MySQL, MongoDB, DynamoDB, Java
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Primary Skills PySpark, Database, SQL, Python,  Secondary Skill Starburst

ETL Hands on experience of building data pipelines. Proficiency in two or more data integration platforms such as Ab Initio Apache Spark Talend and InformationBig Data Experience of big data platforms such as Hadoop, Hive or Snowflake for data storage and processData Warehousing & Database Management Expertise around Data Warehousing concepts, Relational Oracle, MSSQL, MySQL and NoSQL MongoDBDynamoDB database designData Modeling & Design  Good exposure to data modeling techniques; design, optimization and maintenance of data models and data structuresProficient in one or more programming languages commonly used in data engineering such as Python,JavaDevOps Exposure to concepts and enablers - CI/CD platforms, version control,automated quality control managementData Governance  A strong grasp of principles and practice including data quality, security, privacy and compliance










ETL Hands on experience of building data pipelines. 

Proficiency in two or more data integration platforms such as Ab Initio Apache Spark Talend and Information

Big Data Experience of big data platforms such as Hadoop, Hive or Snowflake for data storage and process 

Data Warehousing & Database Management: Expertise around Data Warehousing concepts, Relational Oracle, MSSQL, MySQL and NoSQL MongoDBDynamoDB database design 

Data Modeling & Design: Good exposure to data modeling techniques; design, optimization and maintenance of data models and data structuresProficient in one or more programming languages commonly used in data engineering such as Python,Java 

DevOps: Exposure to concepts and enablers - CI/CD platforms, version control,automated quality control management 

Data Governance: A strong grasp of principles and practice including data quality, security, privacy and compliance