Data Migration Tech Lead: Databricks & DataStage Validation

Tech Mahindra; Dallas (TX); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Paid time off

Job summary

Tech Mahindra in Texas is seeking a data migration specialist to rationalize legacy DataStage environments as they move to Databricks. You will map end-to-end data lineage and identify dead code to streamline migration.

You will implement automated tests with PyTest and Great Expectations, validate schemas and row counts, and collaborate with PySpark teams to ensure zero data loss during cutovers.

Qualifications

• Bachelor’s or higher degree required.
• Experience migrating DataStage to Databricks environments.
• Strong knowledge of automated testing frameworks and data validation.

Responsibilities

• Analyze DataStage exports and metadata to map end-to-end data lineage.
• Identify dead jobs, redundant code, and duplicate logic to streamline migration.
• Explain complex parallel/server PySpark logic to the development team.
• Deploy automated test frameworks to validate data reconciliation between DataStage and Databricks.
• Build scripts to validate schemas, row counts, and transformations across environments.
• Execute regression tests on refactored PySpark code with legacy data.
• Document validation KPIs and sign off on data accuracy before live cutovers.
• Analyze legacy ETL data and metadata for migration readiness.

Skills

Advanced SQL

Python

PySpark

XML/JSON parsing

Great Expectations

PyTest

Databricks

DataStage

Education

Bachelor's degree or higher

Tools

Databricks

PySpark

IBM InfoSphere DataStage

Job description

Tech Mahindra in Texas is seeking a data migration specialist to rationalize legacy DataStage environments as they move to Databricks. You will map end-to-end data lineage and identify dead code to streamline migration.

You will implement automated tests with PyTest and Great Expectations, validate schemas and row counts, and collaborate with PySpark teams to ensure zero data loss during cutovers.