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Mid-level ETL QA role in metro Hyderabad with a notable employer yields medium competition.
ETL testing and data pipeline skills (PySpark, SQL, Hadoop) are broadly transferable across industries, so low sensitivity.
Explicit 6–8 years plus mandatory PySpark, SQL, and Hadoop skills increases shortlisting strictness to high.
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Design, test, and maintain ETL pipelines using Python and PySpark for large-scale data processing.
Validate source-to-target data mappings and ensure data quality across data warehouse solutions.
Collaborate with ETL developers, data engineers, and QA teams to deliver reliable data integration supporting business needs.
6-8 years of relevant experience in ETL testing and data pipeline design.
Strong proficiency in Python; hands-on experience with PySpark and Apache Spark required.
Good knowledge of SQL, data warehousing concepts, and Hadoop ecosystem (HDFS, Hive, etc.).
Employment location: Hyderabad, Telangana, India; full-time position.
Experienced in working with big data technologies like Spark, Hadoop, and Hive within enterprise data engineering contexts.
Hands-on with workflow orchestration tools like Airflow and cloud platforms (AWS/Azure/GCP) considered advantageous.
Able to optimize ETL workflows for performance and scalability while maintaining data accuracy and integrity.