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Popular mid-senior data engineering title, Bengaluru location, and generalist expectations produce medium competition.
Core data engineering skills are transferable, but Databricks and regulated experience increase specialization moderately.
Explicit 6–8 years requirement plus mandatory Databricks, AWS, and MDM skills makes shortlisting strict.
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Design, build, and operate reliable, secure, and cost-efficient cloud-native data pipelines primarily on AWS using modern ETL/ELT approaches.
Ensure production readiness of scalable data platforms enabling analytics and AI, including performance optimization and data quality management.
Collaborate with cross-functional teams and mentor junior engineers while contributing to engineering standards and accelerators.
6-8 years of hands-on data engineering experience.
Strong experience with Databricks (Data Engineering, Delta Lake, Medallion Architecture).
Proven ability to design, build, and support scalable data pipelines and data models within enterprise environments.
Experience with cloud platforms (primarily AWS) and associated data technologies (e.g., PostgreSQL, Aurora).
Experienced engineer capable of taking ownership of complex data challenges in real-world production environments.
Strong background in integrating AI/analytics tools with enterprise data platforms and operationalizing AI-enabled applications.
Experience working in regulated or security-conscious environments, with consulting or client-facing delivery exposure preferred.