Join our Technology & Transformation practice and unlock the power of your data. We guide companies in managing diverse data sources and transforming them into actionable insights for informed decision-making. Our expertise spans business intelligence, data management, performance management, and advanced analytics, including big data, cloud, and machine learning technologies.

This role focuses on ETL testing and quality assurance for data platforms and cloud-based data engineering solutions, driving test strategies and stakeholder engagement across critical data transformation initiatives.

Key responsibilities include designing and implementing automated test frameworks for ETL/ELT pipelines. You will validate source-to-target data reconciliation, transformation logic, and business rules. Develop automated test scripts for data completeness, accuracy, timeliness, and integrity checks.

Perform comprehensive database, file, and API testing across various data formats. Create reusable automation components for essential data validation tasks. Execute regression, integration, and system testing, and analyze test failures, collaborating with data engineers for timely resolution. Validate incremental loads, CDC logic, and historical data migrations, while integrating automation tests with CI/CD pipelines. Prepare detailed test plans, test cases, defect reports, and execution summaries.

We are seeking an experienced ETL Testing and Quality Assurance Engineer with 6-9 years of expertise in ETL pipelines, data platforms, and cloud-based data engineering solutions. A strong understanding of ETL concepts, data warehousing, data lakes, and UNIX is essential.

Proficiency in automation using Python, PyTest, PySpark, Robot Framework, or TestNG is required. Advanced SQL skills for complex data validation are a must. Experience with data platforms like Databricks, Snowflake, Redshift, BigQuery, or Synapse is necessary. Familiarity with ETL tools such as Informatica, Ab Initio, Talend, DataStage, or dbt is also crucial. Hands-on experience with at least one major cloud provider (AWS, Azure, GCP) and CI/CD tools like Jenkins, Azure DevOps, GitHub Actions, or GitLab is expected.

Familiarity with data formats including Parquet, Avro, JSON, CSV, and XML is beneficial. Bonus points for experience with Great Expectations, Deequ, Soda, or Monte Carlo. A Bachelor's degree in Computer Science, Information Technology, or a related field is required.