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Popular Data Engineer role, metro locations, and broad AWS/Databricks skillset increase applicant competition.
Skills are broadly transferable across industries but require specific AWS/Databricks data platform experience.
Strict 8+ years requirement plus mandatory AWS, Databricks, PySpark, and data platform skills.
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Design, develop, and implement complex data engineering solutions on AWS incorporating Databricks.
Optimize and maintain data pipelines leveraging PySpark or Spark Scala, including streaming pipelines for near real-time analytics.
Manage technical design and implementation of data engineering components focusing on modern data architectures like data warehouses, lakes, and lake-houses.
8+ years of hands-on experience in data engineering design, development, and implementation.
Strong proficiency with SQL (including performance tuning), Python programming, and Spark (PySpark or Scala) for data pipelines.
Experience with AWS data engineering services such as Glue, Lambda, Step Functions, Redshift, EMR, and Kinesis.
Location: Chennai or Bangalore preferred.
Demonstrated expertise in building and optimizing near real-time streaming data pipelines on cloud platforms, especially AWS and Databricks.
Experience working with modern data architecture patterns and data governance for analytical platforms.
Familiarity with DevOps practices including CI/CD pipeline automation and version control (Git) for data engineering solutions.