Senior QA Engineer- ETL & Data Platform

Job Description:

Senior QA Engineer – ETL & Data Platform

We are seeking a resource with 6–8 years of experience in any cloud-based database (preferably Databricks) and expertise as a Python-based automation tester, with strong knowledge in ETL automation testing. Please find the position details below.

Role Overview:

We are seeking a Senior QA Engineer (ETL & Data) with 6–8 years of hands-on experience in cloud data platforms (preferably Databricks) and Python-based test automation. The person will be responsible for building robust, scalable test frameworks to validate data ingestion, transformation, and consumption across batch and streaming pipelines. This role is ideal for someone who enjoys digging into data lineage, ensuring data quality at scale, and collaborating closely with Developer, BA, and Architect team.

Responsibilities:

 Own end-to-end test strategy for data pipelines (ingestion → transformation → consumption) across environments (Dev/Test/Prod).
 Design & implement automation frameworks in Python for ETL/ELT validation (schema, DQ, business rules, transformations, aggregations, deduplication, SCD logic).
 Build reusable test libraries for Databricks notebooks/jobs, tables, and SQL validation.
 Implement CI/CD-integrated tests (integration, and regression) for data workloads.
 Covert Manual use cases to automated test cases and provide end to end coverage.

Required Qualifications

 6–8 years in QA/Testing with at least 3+ years focused on data/ETL testing in cloud environments.
 Strong hands-on with Python for test automation (PyTest/Unittest), data manipulation (Pandas, PySpark), and API/CLI automation.
 Practical experience with Databricks (preferred): Notebooks, Jobs, Delta Lake, Unity Catalog, Cluster/SQL Warehouse basics
 Solid SQL skills for complex joins, window functions, aggregations, and performance-aware data validations.
 Strong understanding of ETL/ELT patterns, data modeling concepts (Star/Snowflake, SCDs), data lineage, and metadata management.
 Excellent communication, documentation, and stakeholder collaboration skills.