What are the responsibilities and job description for the Senior Data Quality QA Engineer position at Xoriant Corporation?
Job Title: Senior Data Quality QA Engineer
Location: Minneapolis, MN (Hybrid, 3 days /week onsite)
Duration: Long Term Contract
Description:
The candidate should have hands-on experience with Databricks, AWS Glue, Amazon Redshift, SQL, Python, and cloud-based data platforms. Experience testing data migration, data transformation, reporting, and AI-enabled development workflows is highly preferred.
Responsibilities
- Design and execute end-to-end test strategies for data engineering and analytics projects.
- Validate ETL/ELT pipelines built using AWS Glue and Databricks.
- Perform data quality testing across multiple data sources and data warehouses.
- Develop SQL queries to validate source-to-target data transformations.
- Verify data completeness, consistency, accuracy, duplicates, and reconciliation.
- Perform testing of Amazon Redshift data warehouse solutions.
- Validate batch and incremental data loads.
- Create automated data validation frameworks using Python and SQL.
- Work closely with Data Engineers, AI Developers, Product Owners, and Business Analysts.
- Review business requirements and create detailed test scenarios and test cases.
- Identify, document, and track defects through resolution.
- Perform regression, integration, system, and user acceptance testing.
- Support CI/CD pipelines and automated testing processes.
- Use AI-assisted development tools (such as GitHub Copilot, Amazon Q, or similar AI coding assistants) to improve test automation, SQL generation, and productivity.
- Ensure data governance, data lineage, and quality standards are maintained.
- Participate in sprint planning, backlog grooming, and Agile ceremonies.
- Prepare test execution reports and quality metrics for stakeholders.
Required Skills
- 7–8 years of experience in Software QA with strong focus on Data Quality Testing.
- Strong SQL skills with experience writing complex queries.
- Hands-on experience with Databricks.
- Experience testing AWS Glue ETL pipelines.
- Experience validating data in Amazon Redshift.
- Strong knowledge of ETL/ELT testing methodologies.
- Experience with Python for test automation and data validation.
- Good understanding of cloud platforms, preferably AWS.
- Experience validating structured and semi-structured data (CSV, JSON, Parquet, Delta).
- Knowledge of data reconciliation and source-to-target validation.
- Experience using defect management tools such as Jira.
- Experience with Git and CI/CD pipelines.
- Strong analytical and troubleshooting skills.
- Excellent communication and documentation skills.
Preferred Skills
- Experience with AI-enabled software development and testing.
- Experience using GitHub Copilot, Amazon Q, ChatGPT, or similar AI tools.
- Knowledge of Apache Spark and PySpark.
- Experience with Delta Lake.
- Familiarity with Airflow or other workflow orchestration tools.
- Experience with Tableau, Power BI, or QuickSight report validation.
- Exposure to data governance and data quality tools.
- Experience working in Agile/Scrum environments.
Nice to Have
- Experience with machine learning data validation.
- Knowledge of Great Expectations or similar data quality frameworks.
- AWS Certification or Databricks Certification.
- Experience with large-scale enterprise data migration projects.
Salary : $50 - $55