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Tier-1 bank, mid-level data engineer in metro with broad demand and common skillset drives high competition.
Databricks and cloud skills are transferable, but financial governance (BCBS239) adds moderate industry specificity.
Role requires specific Databricks, Spark, cloud, Python, and governance skills, enforcing strict technical filters.
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Design, develop, and deploy scalable batch and real-time data pipelines using Python, PySpark, Spark SQL, and Databricks.
Deploy and maintain Databricks workspaces on AWS or GCP cloud environments with secure integrations and performance optimization.
Act as technical lead within Agile teams, driving best practices in code quality, CI/CD, data governance, and mentoring junior engineers.
Strong proficiency in Python (including pandas, pytest) and advanced SQL including window functions and query optimization.
Minimum 3 years hands-on experience with Databricks and Apache Spark in distributed cluster environments processing multi-terabyte datasets.
Experience with cloud platforms AWS or GCP, including cloud-native components such as S3/GCS, IAM, and related tools.
Work Experience Required: Minimum 3 years on Databricks and Spark based development; notice period: Not explicitly mentioned in the JD.
Deep expertise in Delta Lake features (ACID transactions, Delta Live Tables, Unity Catalog) and cloud-native data engineering integrations.
Experienced technical leader capable of enforcing coding standards, leading peer reviews, and mentoring team members within Agile environments.
Proven ability to troubleshoot complex distributed systems performance issues and implement rigorous data quality and governance controls.