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PwC brand, metro Bangalore, mid-level data engineer title and broad AWS skillset increase applicant competition.
Requires AWS, PySpark, CDC, EOD and enterprise replication experience, making cross-industry transferability limited.
Explicit 5–8 years requirement plus mandatory AWS, SQL, PySpark, and production-readiness demands heighten screening strictness.
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Design, build, and optimize scalable ETL/ELT data pipelines using AWS services like Glue, Step Functions, Lambda, and DMS.
Implement data ingestion strategies ensuring referential integrity, idempotency, and recovery for high-volume processing.
Develop monitoring, validation, and reconciliation frameworks to maintain production readiness and throughput for end-of-day workloads.
5–8 years overall work experience with at least 3 years in data engineering, data integration, or related roles.
Expert-level SQL, strong proficiency in Python and PySpark, with hands-on ETL pipeline and orchestration experience.
Experience with AWS cloud-native services Glue, Step Functions, Lambda, and DMS essential.
Bachelor’s degree in Engineering, Technology, MBA, or equivalent qualification required.
Proven track record of building resilient, idempotent ingestion frameworks handling high-volume, time-sensitive data loads.
Strong operational focus including monitoring, alerting, and maintenance of runbooks for data pipelines.
Comfortable working with ACID-compliant data ingestion, schema evolution, CDC patterns, and cloud-native architecture on AWS.