Data Quality Engineer Automation & Validation

Job Title:

Data Quality Engineer Automation & Validation

Job Description:

We are looking for a Data Quality Engineer with strong experience in data validation, quality assurance, and automation testing to ensure data accuracy, integrity, and consistency across systems. The ideal candidate will have a deep understanding of automated testing frameworks and scripting, along with strong analytical and troubleshooting skills to resolve data-related issues.

Required Skills:

• Strong understanding of data quality principles, data validation techniques, and data governance.
• Hands-on experience with automated testing frameworks(e.g., Selenium, TestNG, JUnit).
• Proficiency in scripting languageslike Python, JavaScript, or Shell.
• Familiarity with data issue tracking and reporting tools(e.g., JIRA).
• Excellent problem-solving and analytical skillsto troubleshoot data anomalies.
• Strong communication skills to clearly document and report findings.

Key Responsibilities:

• Perform comprehensive data validation and quality checksacross multiple data sources and systems to ensure data integrity and consistency.
• Identify and document data discrepancies, and work cross-functionally to resolve issues efficiently.
• Design, develop, and maintain automated test casesusing frameworks like Selenium, TestNG, or JUnit.
• Write test scripts using Python, JavaScript, or Shell scriptingto support automated data validation efforts.
• Use issue tracking tools such as JIRAto document and monitor defects, ensuring proper resolution and closure.
• Collaborate with data engineers, analysts, and developers to establish data quality standards and best practices.
• Develop reusable scripts and frameworks for continuous integration of data quality into ETL/ELT pipelines.
• Proactively identify areas for data improvement and recommend enhancements to ensure reliable and high-quality data delivery.

Preferred Qualifications:

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Experience in working with data pipelines, ETL/ELT processes, and cloud platforms (AWS, Azure, Google Cloud Platform) is a plus.
• Knowledge of SQL and relational databases is an advantage.