Back
Strong Big4 brand, mid-level seniority, metro location, and broad tooling needs drive high competition.
Specialized ETL and data-platform testing increases domain bias, though QA fundamentals remain transferable.
Explicit 6-9 years plus mandatory ETL/data-testing skills and specific tooling increases strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and deploy automated test frameworks for ETL/ELT pipelines ensuring data accuracy, completeness, and integrity.
Coordinate with process owners to understand business workflows and design automation test flows, including executing regression and integration tests for data pipelines.
Analyze test failures, perform root cause analysis, and collaborate with data engineers to resolve issues while maintaining documentation for UAT and production phases.
6-9 years of relevant experience in ETL testing and automation framework development.
Bachelor's or Master's degree in Engineering, Computer Science, MCA, or related field.
Strong expertise in ETL concepts, data warehousing, data lakes, and UNIX environments.
Advanced SQL skills (BigQuery preferred) and proficiency with automation tools such as Python, PyTest, Robot Framework, or TestNG.
Experienced in designing and implementing automated test frameworks specifically for data platforms like Databricks, Snowflake, Redshift, BigQuery, or Synapse.
Capable of validating complex data transformations, incremental loads, CDC logic, and historical data migrations in diverse ETL tool environments such as Informatica, Ab Initio, Talend, DataStage, or DBT.
Proficient in collaborating cross-functionally to translate business requirements into test plans with a focus on scalable and maintainable automation solutions.