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Mid-level data engineer in Bangalore with broad, popular stack and generalist requirements increases candidate competition.
Core data engineering skills like Python, SQL, and pipeline design are highly transferable across industries.
Explicit 3+ years and mandatory Databricks, Spark, Airflow, CDC, Python, SQL, and TDD increase screening strictness.
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Own the reliability, performance, and scalability of operational data pipelines powering the life sciences catalog.
Reduce technical debt by replacing reactive patches with designed, testable logic and build observability, automated testing, and monitoring infrastructure.
Translate evolving business requirements into durable pipeline logic, own code versioning, deployment, and incident response end-to-end.
3+ years experience as a Data Engineer with solo or primary ownership of production pipelines.
Strong Python skills for data engineering, transformations, and testing discipline.
Proficient in SQL with ability to write correct queries and refactor anti-patterns.
Experience with Databricks, Delta Lake, Airflow, CDC patterns for real-time synchronization, and building low latency data APIs.
Experienced in independently managing complex data engineering pipelines with end-to-end ownership including incident response and deployment.
Able to design systems that are maintainable and scalable under ambiguous requirements and changing business needs.
Has expertise in the specified tech stack (BigQuery, Databricks, Spark/PySpark, AWS/GCP) and adheres to test-driven development discipline.