Data Quality Automation Engineer

About the role

We are 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.

Responsibilities

• 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.