Back
Known employer brand, popular Data Engineer title, and Bangalore metro drive high candidate competition.
Skills are transferable across industries but platform-specific Databricks/BigQuery experience raises domain sensitivity.
Explicit 7–10 years plus required Databricks, BigQuery, Python, SQL increases screening strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead technical direction and standards for the data engineering team, including architecture decisions, code review, and quality assurance.
Design, build, and maintain scalable production data pipelines with end-to-end ownership using Databricks and Google BigQuery.
Continuously adopt and apply latest features and capabilities from Databricks and BigQuery to improve pipeline performance, cost efficiency, and scalability.
7–10 years of professional experience in data engineering with production-grade pipeline ownership.
Strong hands-on experience with Databricks platform and practical knowledge of medallion architecture (bronze, silver, gold).
Strong hands-on experience with Google BigQuery including adoption of new features like BQML and materialized views.
Proficiency in Python, SQL, and Git version control.
Experienced technical leader who has led teams on architecture and code quality, capable of mentoring and coaching engineers.
Deep expertise in data pipeline design, data modeling (fact and dimension models), and building solutions across diverse, evolving source systems.
Adaptable and proactive in evaluating and integrating emerging data engineering tools and technologies, especially in Databricks and BigQuery ecosystems.