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PwC brand, Bangalore mid-level AWS Data Engineer with common skills drives high applicant competition.
Core AWS data engineering skills are transferable across industries, though SAP/enterprise replication exposure slightly raises domain specificity.
Explicit 5–8 years requirement plus mandatory AWS, PySpark, and SQL skills make shortlisting highly strict.
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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 for snapshots and delta loads ensuring data integrity, idempotency, and recovery.
Build monitoring, validation, and reconciliation frameworks to support high-volume and time-sensitive data processing workloads (especially EOD).
5-8 years total experience with at least 3 years in data engineering or related roles.
Proficiency in AWS services (Glue, Step Functions, Lambda, DMS) and strong skills in SQL, Python, and PySpark.
Bachelor’s degree or equivalent (BE, B.Tech, ME, M.Tech, MBA, MCA) is preferred.
Experience with production readiness, ACID-compliant data ingestion, schema evolution, and CDC patterns.
Experienced in building resilient and idempotent data ingestion frameworks handling high-volume EOD workloads.
Strong operational focus including monitoring, alerting, and runbook maintenance expertise.
Familiarity with cloud-native architectures and AWS data engineering best practices to ensure scalable and efficient data solutions.