Data Quality Engineer (39642)

Join a dynamic team as a Data Quality Engineer to analyze business needs and create detailed test plans for Azure Synapse, PowerBI, and related technologies. You'll lead ETL testing, data validation, and automation using PyTest and PySpark. Ensure the integrity of Delta Lake data and perform critical file comparisons. Collaborate with cross-functional teams to prioritize and execute tests efficiently. Candidates should have 2+ years of QA experience, Python proficiency, and hands-on skills in SQL and big data formats like Delta and Parquet. Familiarity with Azure DevOps and agile methods is a plus.

🚀 Project
- analyzing business requirements and estimating testing effort
- developing and executing comprehensive test plans for Azure Synapse, PowerBI, and other data technologies
- collaborating with technical teams to define, prioritize, and execute testing activities
- applying best practices in ETL testing and data validation
- building data quality checks using PyTest and PySpark
- validating Delta Lake data and performing file comparisons to ensure integrity

🎯 Skills
- 2+ years of experience as a Quality Analyst
- strong ETL pipeline testing and test data management skills
- proven ability to interpret business requirements and develop test plans
- experience with Delta Lake validation and file comparison
- proficient in Python, including PyTest and PySpark for test automation
- skilled in testing PowerBI reports for data accuracy, functionality, and presentation
- hands-on experience with Azure Synapse, Data Factory (ADF), and Databricks
- familiar with big data processes: ingestion, analysis, curation, and pipelines
- experience creating quality checks for big data workflows
- proficient in SQL and writing queries in SQL Server
- knowledge of big data storage formats such as Delta and Parquet

💡 Nice to have
- QA Leadership experience
- knowledge and working experience with Azure DevOps
- agile methodology working experience