Data Test Engineer

• Design, develop, and maintain robust ETL/ELT pipelines to process large volumes of structured and unstructured data using Azure Data Factory, PySpark, and SQL-based tools
• Collaborate with data architects and analysts to understand transformation requirements and implement business rules correctly
• Develop and execute complex SQL queries to validate, transform, and performance-tune data workflows
• Perform rigorous data validation including source-to-target mapping (S2T), data profiling, reconciliation, and transformation rule testing
• Conduct unit, integration, regression, and performance testing for data pipelines and storage layers
• Automate data quality checks using Python and frameworks like Great Expectations, DBT, or custom-built tools
• Monitor data pipeline health and implement observability through logging, alerting, and dashboards
• Integrate testing into CI/CD workflows using tools like Azure DevOps, Jenkins, or GitHub Actions
• Troubleshoot and resolve data quality issues, schema changes, and pipeline failures
• Ensure compliance with data privacy, security, and governance policies
• Maintain thorough documentation for data flows, test logic, and validation processes

• 4+ years of experience in Data Engineering and Data/ETL Testing
• Strong expertise in writing and optimizing SQL queries (joins, subqueries, window functions, performance tuning)
• Proficiency in Python or PySpark for data transformation and automation
• Hands-on experience with ETL tools such as Azure Data Factory, Talend, SSIS, or Informatica
• Familiarity with cloud platforms, preferably Azure
• AWS or GCP is a plus
• Experience working with data lakes, data warehouses (Snowflake, BigQuery, Redshift), and modern data platforms
• Knowledge of version control systems (Git), issue tracking tools (JIRA), and Agile methodologies
• Exposure to data testing frameworks like Great Expectations, DBT tests, or custom validation tools
• Experience integrating data testing into CI/CD pipelines

Familiarity with Airflow, Databricks, BI tools (Power BI, Tableau), and metadata management practices

• Competitive salary aligned with industry standards
• Hands-on experience with enterprise-scale data platforms and cloud-native tools
• Opportunities to work on data-centric initiatives across AI, analytics, and enterprise transformation
• Access to internal learning accelerators, mentorship, and career growth programs
• Flexible work culture, wellness initiatives, and comprehensive health benefits