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Popular Data Engineer title, mid-level (3+ years) requirement, and Bengaluru metro increase competition.
Strong Databricks, Delta Lake, and Unity Catalog specialization limits cross-industry transferability.
Explicit 3+ years plus 1+ year Databricks and required PySpark/Delta Lake skills enforce strict shortlisting.
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Design, develop, and tune scalable data pipelines and Lakehouse solutions on Databricks with focus on performance and cost optimization.
Implement and operationalize Unity Catalog for data governance including access control, lineage, and security.
Build monitoring, self-healing automation, and contribute to CI/CD workflows for Databricks assets using DevOps best practices.
Bachelor or Master’s degree in Computer Science, Information Technology or equivalent experience.
3+ years of data engineering experience including at least 1 year hands-on Databricks in enterprise settings.
Strong Python (PySpark) and SQL skills; ability to tune Spark workloads for cost and performance.
Working knowledge of Databricks Lakehouse architecture, Delta Lake, Unity Catalog, workflow orchestration, and CI/CD practices for data workloads.
Experienced in tuning Databricks workloads with a performance-engineering mindset measuring and optimizing cost and performance.
Familiar with Databricks-native AI capabilities and automation frameworks to build self-healing systems.
Has operational ownership approach emphasizing platform quality, cost controls, reliability, and effective communication with technical and business stakeholders.