Back
Mid-level Databricks data role, metro location, and common 4–6 year experience increase applicant density.
Core data engineering skills are transferable, but DB2/mainframe migration requirements raise domain specificity.
Explicit 4–6 year requirement plus mandatory Databricks, PySpark, SQL, and migration skills make screening strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own design, development, and support of scalable ETL/ELT data pipelines using Databricks, PySpark, Python, SQL, and AWS cloud services.
Lead and execute migration of DB2 schemas and data from mainframe to AWS PostgreSQL ensuring data integrity and business continuity.
Optimize and monitor Databricks workflows, perform data validation, reconciliation, and maintain data quality during migration and modernization initiatives.
4-6 years of experience in relevant data engineering with strong hands-on skills in Databricks, PySpark, Python, SQL, and PostgreSQL.
Experience in ETL/ELT pipeline development, AWS cloud data services (S3, RDS, Glue), and DB2 database migration to AWS PostgreSQL.
Proven expertise in SQL performance tuning, data modeling, and database administration concepts.
Work Location: Pune, India. Work Experience Required: 4-6 years.
Experienced professional in data migration and modernization projects involving mainframe DB2 to cloud PostgreSQL transitioning.
Strong technical maturity in cloud-based data engineering ecosystems combining Databricks, AWS, and open-source tools with CI/CD pipelines.
Able to plan and lead migration cutover, testing, and production deployment with cross-functional collaboration ensuring data governance and security standards.