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Tier-1 brand, Pune metro, and common Data Engineer title increase competition.
Databricks, Delta Lake, Spark expertise plus financial governance needs makes background fit highly sensitive.
Multiple mandatory Databricks, Spark, Python, cloud, and governance requirements make shortlisting highly strict.
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Lead design, development, and deployment of scalable batch and real-time ETL/ELT data pipelines using Python, PySpark, Spark SQL, and Databricks.
Manage Databricks cloud infrastructure integration including workspace deployment on AWS or GCP, secure cloud storage access, and serverless query engines.
Provide technical leadership by enforcing best practices, mentoring junior engineers, optimizing performance, and ensuring data governance compliance including financial regulations like BCBS 239.
Strong production experience with Python, advanced SQL, Apache Spark (PySpark), and Databricks (minimum 3 years hands-on).
Experience deploying Databricks on AWS or GCP with proficiency in cloud-native components (S3/GCS, IAM, EMR, Athena, BigQuery etc).
Knowledge of data warehousing concepts including dimensional modeling, slow-changing dimensions, and Medallion architecture.
Work Experience Required: Minimum 3 years in Databricks data engineering.
Technical expert comfortable with managing distributed computing environments and large-scale data pipelines across cloud platforms.
Experienced leader skilled in setting coding standards, leading peer reviews, and mentoring data engineering teams in Agile/Scrum settings.
Deep understanding of data governance and regulatory compliance in financial services with operational responsibility for data quality and security.