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Senior requirement reduces applicants, but broad data engineering skills and metro location keep competition moderate.
Core data engineering skills transfer across industries, but financial regulations and governance increase sensitivity moderately.
Explicit 8+ years, leadership and mandatory cloud/data tooling create stringent shortlisting filters.
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Lead and develop a high performing team responsible for designing, building, and modernizing cloud-native data ingestion, integration, and API services.
Architect and migrate legacy SQL/ETL pipelines to scalable, governed AWS-native batch, streaming, and event-driven data pipelines.
Shape the technical roadmap, drive engineering standards, and collaborate cross-functionally to ensure reliable, secure, and automated data availability.
8+ years of experience in data engineering, software engineering, or cloud engineering.
Bachelor’s degree in Data Science, Computer Science, or related field; Master’s degree preferred.
Hands-on experience with AWS cloud data lake services (S3, Glue), data lake design patterns, programming in Python/SQL, pipeline orchestration (Airflow, Step Functions), and DevOps tools (Terraform/CloudFormation, CI/CD).
Experience leading and developing high performing teams.
Strong architectural instincts with demonstrated ability to modernize legacy data pipelines into cloud-native implementations on AWS.
Experience driving engineering excellence and standards in a federated data product or data mesh environment.
Background collaborating with cross-functional teams including architecture, analytics, AI, and governance in regulated industries (financial services preferred).