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Popular data-engineer role in Bangalore with specific AWS/PySpark skills attracts moderate applicant density.
Data engineering skills with cloud and Spark are highly transferable across industries.
Multiple mandatory data-engineering technologies (PySpark, Glue, Snowflake, Kafka) increase technical filter strictness.
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Design, develop, and optimize ETL and data pipelines using PySpark, AWS Glue, and AWS data services (RDS, DynamoDB, Kafka).
Build and maintain batch and real-time streaming data ingestion pipelines implementing Medallion architecture and Data Lake solutions using Hudi.
Develop complex SQL queries, support data validation, performance tuning, and troubleshoot pipelines ensuring scalable and reliable data solutions.
Strong hands-on experience with PySpark, AWS Glue, and AWS Data Engineering in ETL projects.
Excellent SQL programming skills and knowledge of Snowflake.
Experience with Kafka, AWS RDS, DynamoDB, and data pipeline development.
Educational Qualification: B.E/B.Tech; Work Location: Bangalore with 5 days office attendance; Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and optimizing data engineering pipelines in cloud environments, specifically AWS.
Familiar with Medallion architecture, Data Lakes using Hudi, and working with batch and streaming data.
Comfortable working in cross-functional teams delivering scalable data solutions in an enterprise or consulting context.