Data Quality Automation Engineer

Job Description Client is seeking a Data Quality Automation Engineer to build and scale automated data quality solutions that ensure the accuracy, consistency, and reliability of enterprise data. In this hands-on role, you'll develop automation frameworks, integrate data quality validation into modern data pipelines, and partner with cross-functional teams to ensure trusted data powers analytics, reporting, and AI initiatives. You'll play a key role in establishing automated testing practices, improving data governance, and supporting Agile delivery teams through quality engineering and continuous improvement. Data Quality Automation • Design, develop, and maintain automated data validation frameworks. • Validate data accuracy, completeness, consistency, and integrity across enterprise data pipelines. • Create automated reconciliation and quality validation processes. • Troubleshoot and debug automation scripts in local development environments. Pipeline Integration & Monitoring • Integrate automated data quality checks into CI/CD pipelines and orchestration workflows. • Build anomaly detection, data drift monitoring, and automated alerting capabilities. • Proactively identify data issues before they impact downstream analytics or AI solutions. • Support continuous monitoring of data quality KPIs and service levels. Quality Engineering • Develop test plans, test cases, and validation strategies for data engineering initiatives. • Execute functional, regression, and automated testing. • Identify, document, and track software defects through resolution. • Analyze test failures, review logs, and collaborate with developers to resolve issues. • Ensure appropriate test coverage across Agile sprint deliverables. Collaboration & Governance • Partner with data engineers, data scientists, platform teams, and business stakeholders to define data quality standards. • Translate governance and security policies into automated validation rules. • Support compliance, auditability, and enterprise data governance initiatives. • Participate as an active member of Agile Scrum teams focused on continuous delivery and quality. Requirements • Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, or a related field. • 2–5 years of experience in data engineering, data quality, software quality assurance, or test automation. • Hands-on experience with C#, SQL, Python (PySpark), Microsoft Fabric, and the Redgate toolset. • Experience building automated testing solutions for data platforms. • Experience with Visual Studio, Azure DevOps, GitHub, and SQL Server. • Experience working within Agile development environments using CI/CD practices. • Ability to analyze test failures, troubleshoot issues, and document detailed defects. • Strong written and verbal communication skills with both technical and non-technical stakeholders. • Ability to work independently and collaboratively in a hybrid environment. Preferred Qualifications • Experience using the Playwright automation framework (1+ year preferred). • Familiarity with Git version control. • Experience with data pipeline validation and automated reconciliation testing. • Knowledge of data governance, security, and compliance best practices. • Experience supporting enterprise analytics or AI/ML data platforms. • Passion for software quality engineering and continuous improvement.