QA Engineer
14 hours ago
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit
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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