DATA QA Engineer

Job Summary :

As a Data QA Engineer , you will be responsible for verifying the accuracy and quality of data across systems and processes. You will design and implement test cases, conduct data validation, and ensure the quality of data in ETL processes, data pipelines, data warehouses, and business intelligence systems. The role requires strong analytical skills and attention to detail to ensure data integrity, reliability, and consistency in a dynamic, data-driven environment.

Key Responsibilities :

1. Data Testing and Validation :

• Develop and execute comprehensive test plans, test cases, and scripts for data validation across various stages of the data lifecycle.
• Perform data validation and verification for different data sources, including databases, APIs, data warehouses, and data lakes.
• Validate data accuracy, completeness, consistency, and timeliness across multiple systems, ensuring that data is correct and meets business requirements.
• Perform reconciliation between different datasets to identify discrepancies and data quality issues.

2. ETL Testing :

• Test the data integration, transformation, and extraction processes within ETL pipelines to ensure that the data is properly extracted, transformed, and loaded into the target system.
• Verify that data transformations are applied correctly, ensuring that the final dataset matches the required format, structure, and business rules.
• Ensure that data integrity is maintained during ETL processes, including handling null values, duplicates, and outliers.

3. Data Quality Assurance :

• Implement data quality checks and monitor the performance of data systems to ensure ongoing accuracy and reliability.
• Identify, report, and track data quality issues and work with data engineers and other stakeholders to resolve them.
• Establish and enforce data quality standards, ensuring compliance with data governance policies.
• Create automated data validation scripts to streamline quality checks and reduce manual intervention.

4. Automation and Tooling :

• Automate data testing processes using testing frameworks and tools, such as Selenium , JUnit , Apache JMeter , or custom scripts.
• Develop and maintain test automation scripts for data validation, including database testing, data integrity checks, and data load verification.
• Use data profiling tools to assess the completeness, uniqueness, consistency, and distribution of data.

5. Reporting and Documentation :

• Document test plans, test cases, and test results, providing clear and detailed reports on the status of data quality and test execution.
• Work closely with cross-functional teams to communicate test results, including identifying issues, risks, and recommendations.
• Provide regular updates on testing progress and issue resolution to stakeholders, including developers, product managers, and business analysts.

6. Collaboration and Continuous Improvement :

• Collaborate with data engineers, data scientists, and product teams to understand data requirements and improve data quality processes.
• Participate in design and code reviews to ensure that data handling and transformations meet quality standards.
• Continuously learn new techniques and tools for data validation and quality assurance, applying them to improve existing processes.

7. Performance and Scalability Testing :

• Conduct performance and scalability tests for data processing systems to ensure they handle large volumes of data efficiently.
• Test data pipelines and data storage solutions to ensure they can scale as data volumes and complexity increase.
• Identify bottlenecks and work with engineering teams to optimize data systems for performance.

Required Skills and Qualifications :

• Education : Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent work experience.
• Experience :
  • Proven experience as a Data QA Engineer , Data Analyst , or in a similar role focused on data quality testing.
  • Hands-on experience with ETL testing , data validation , and data transformation .
  • Familiarity with database management systems (e.g., SQL Server , MySQL , Oracle , PostgreSQL ) and data storage technologies.
  • Experience writing SQL queries for data validation, reporting, and querying large datasets.
  • Understanding of data pipelines, data warehousing, and data integration processes.

Preferred Skills :

• Experience with data profiling and data quality tools such as Informatica Data Quality , Talend , or Apache Nifi .
• Familiarity with big data technologies (e.g., Hadoop , Spark , Kafka ) and cloud platforms (e.g., AWS , Azure , Google Cloud ).
• Experience with automation frameworks such as Selenium , JUnit , or Apache JMeter .
• Knowledge of Agile methodologies and tools (e.g., JIRA , Confluence ).
• Experience with version control tools (e.g., Git ).

Personal Attributes :

• Strong analytical and problem-solving skills, with the ability to spot data discrepancies and inconsistencies.
• High attention to detail and commitment to maintaining high data quality standards.
• Excellent communication skills to interact with cross-functional teams and explain technical issues to non-technical stakeholders.
• A proactive and self-driven approach to identifying areas for improvement and continuously improving data testing processes.
• Ability to manage multiple priorities and work effectively in a fast-paced environment.

Work Environment :

• The Data QA Engineer role will typically be part of an Agile development or data engineering team.
• The position may require occasional off-hours support for urgent testing needs, especially during data migrations or large-scale projects.
• The role can be remote or office-based, depending on the company's policies.

Reporting Structure :

• The Data QA Engineer typically reports to the QA Manager , Data Engineering Manager , or Head of Data Quality .
• The role involves collaboration with data engineers, data analysts, product teams, and business intelligence teams.