What are the responsibilities and job description for the Data Quality Automation Engineer position at BravoTECH?
Location: Hybrid
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.
What You'll Do
Data Quality Automation
Join a collaborative engineering team where you'll help improve enterprise data quality through automation and modern testing practices. Your work will directly support trusted analytics, data-driven decision-making, and AI initiatives while helping shape the organization's quality engineering standards.
If you're passionate about data quality, automation, and building reliable data platforms, we'd love to hear from you. Apply today!
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.
What You'll Do
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.
- 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.
- 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.
- 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.
- 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.
- 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.
Join a collaborative engineering team where you'll help improve enterprise data quality through automation and modern testing practices. Your work will directly support trusted analytics, data-driven decision-making, and AI initiatives while helping shape the organization's quality engineering standards.
If you're passionate about data quality, automation, and building reliable data platforms, we'd love to hear from you. Apply today!