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Job DescriptionWe are looking for an experienced QA Automation Engineer with strong expertise in Python-based automation, ETL and database testing, and Big Data validation within Azure Fabric environments. The ideal candidate will be responsible for ensuring high-quality data workflows and automation across complex data pipelines and analytics platforms.
Responsibilities
- Design, develop, and maintain automation frameworks using Python for data validation and workflow testing.
- Perform ETL testing to validate data extraction, transformation, and loading processes across multiple data sources.
- Conduct Database and Big Data testing using SQL and other relevant tools to ensure data integrity and performance.
- Validate end-to-end data pipelines across Azure Data Fabric, Azure Synapse, and Azure Data Factory.
- Collaborate with Data Engineering and Development teams to identify quality gaps, define test strategies, and improve automation coverage.
- Develop and execute test cases, test scripts, and regression suites for large-scale data applications.
- Perform data reconciliation and validation in distributed environments (Hadoop, Spark, or Databricks).
- Participate in CI/CD automation and support quality gates in Azure DevOps pipelines.
- Document test results, defects, and ensure traceability from requirements to validation.
- 3+ years of experience in QA Automation with a strong background in data testing.
- Hands-on experience in Python-based automation frameworks (PyTest, Unittest, or custom-built).
- Strong SQL skills for data validation, profiling, and complex query testing.
- Proven experience in ETL testing and validation of data flows across staging, transformation, and target layers.
- Experience in Big Data testing (Spark, Hive, HDFS, Databricks, or similar technologies).
- Knowledge of Azure Data Fabric, Azure Data Factory, Synapse, and Data Lake.
- Good understanding of data warehousing concepts, data modeling, and schema validation.
- Experience working with CI/CD pipelines, Git, and Azure DevOps.
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