Job Description
Job Description
- Design and execute Data Quality Rules, Data Profiling, and Test Plans based on business requirements.
- Perform in-depth Data Validation and Reconciliation, identify data anomalies, and track defects through resolution.
- Test Data Pipeline and ETL processes to ensure data transformation aligns with business logic.
- Develop and maintain automated data quality checks using SQL and Python to reduce manual testing.
- Collaborate closely with Data Engineers, Data Analysts, Product Owners, and Development Teams in an Agile/Scrum environment.
- Define and review Acceptance Criteria and assess data-related risks.
- Support and mentor Junior Data Quality Assurance team members and share data quality best practices.
Requirement
Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or related fields.
- 2–5 years of experience in Data QA, Data Engineering, or Data Analysis.
- Experience in ETL and Data Pipeline Testing.
- Strong knowledge of Advanced SQL for data analysis, validation, and reconciliation.
- Good understanding of Relational Databases and Data Warehouse concepts.
- Experience using Python (e.g., Pandas) for data analysis and quality validation.
- Familiarity with Data Catalog or BI Tools.
- Experience working in an Agile/Scrum environment.
- Strong analytical, problem-solving, communication, and collaboration skills.
- Ability to work independently and provide guidance or mentoring to junior team members.
