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High due to Tier-1 brand, mid-level generalist data engineer title, and Bangalore metro location.
Medium because core data engineering skills transfer across industries, but AWS and enterprise CDC specifics narrow fit.
High due to explicit 5–8 years and mandatory AWS, SQL, Python, PySpark, and production-readiness requirements.
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Design, build, and optimize scalable ETL/ELT data ingestion pipelines using AWS services like Glue, Step Functions, Lambda, and DMS.
Ensure production readiness by implementing referential integrity, idempotency, recovery mechanisms, and managing high-volume EOD ingestion workloads.
Develop monitoring, validation, and reconciliation frameworks to maintain data pipeline robustness and performance.
5-8 years total work experience with minimum 3 years in data engineering, data integration, or related roles.
Strong expertise in SQL, Python, and PySpark with advanced SQL performance optimization skills.
Hands-on experience with AWS data engineering tools: Glue, Step Functions, Lambda, and DMS.
Bachelor's degree required (BE/B.Tech preferred), MBA or equivalent also accepted.
Experienced in building resilient, idempotent production data pipelines supporting high-volume, time-sensitive workloads such as EOD batch processing.
Skilled in enforcing ACID-compliant data ingestion and implementing schema evolution with CDC patterns.
Comfortable owning end-to-end solution delivery with strong operational discipline including monitoring, alerting, and runbook maintenance.