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Tier-1 brand, mid-level data engineer role, Bangalore metro, and broad AWS/SQL/Python skills increase competition.
Core AWS, SQL and PySpark skills transfer across industries, though SAP and advisory experience increases domain specificity.
Explicit 5–8 years plus mandatory AWS, SQL, Python and production-readiness requirements.
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Design, build, and optimize scalable ETL/ELT data ingestion pipelines using AWS services such as Glue, Step Functions, Lambda, and DMS.
Ensure production readiness including referential integrity, processing order, idempotency, and recovery mechanisms for high-volume data workloads.
Develop monitoring, validation, and reconciliation frameworks to manage large-scale end-of-day (EOD) ingestion processes.
5–8 years overall experience with minimum 3 years relevant in data engineering or data integration roles.
Expert-level skills in SQL development and performance optimization, strong proficiency in Python and PySpark.
Hands-on experience with AWS data engineering tools including Glue, Step Functions, Lambda, and DMS.
Bachelor’s degree required (BE, B.Tech, MBA, MCA, or equivalent).
Experienced in building resilient, idempotent, and ACID-compliant ingestion frameworks supporting high-volume and time-sensitive workloads.
Strong operational mindset with proven ability to implement monitoring, alerting, and maintain runbooks for production data pipelines.
Familiarity with cloud-native architectures and data integration patterns such as CDC, schema evolution, and direct ingestion into Aurora.