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Tier-1 brand, metro Bangalore, mid-level generalist data engineer role with broad AWS skillset.
Core data engineering skills are transferable, though EOD, CDC and SAP exposures add moderate industry specificity.
Explicit 5–8 years plus mandatory SQL, Python, PySpark, and AWS production-readiness requirements increase filtering rigidity.
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Design, develop, and optimize scalable ETL/ELT data pipelines using AWS services including Glue, Step Functions, Lambda, and DMS.
Implement data ingestion strategies supporting snapshots, delta loads, and ensure data integrity, idempotency, and recovery.
Build monitoring, validation, and reconciliation frameworks for high-volume, time-sensitive production data workloads, especially EOD ingestion.
5–8 years total experience with minimum 3 years in relevant data engineering or data integration roles.
Expert-level skills in SQL with strong proficiency in Python and PySpark.
Hands-on experience with AWS data engineering tools: Glue, Step Functions, Lambda, DMS.
Educational qualifications: Bachelor’s or Master’s in Engineering, Technology, MBA, or MCA (or equivalent).
Experienced in building resilient, idempotent, and ACID-compliant data ingestion pipelines for production environments.
Strong operational mindset with skills in pipeline monitoring, alerting, and maintaining runbooks for high-throughput environments.
Familiarity with complex data engineering patterns including schema evolution, CDC, and cloud-native architectures on AWS.