Data QA Analyst at Tata Consultancy Services

Job Title

Location

Salary Range

About the role

Data QA / ETL Testing Analyst (Entry-Level)

Responsibilities

• Aid in data testing and validation activities for ETL pipelines and data applications.
• Support requirement analysis and gain an understanding of data flows, transformations, and business rules.
• Help design and execute test cases for data validation, reconciliation, and data quality checks.
• Use SQL and basic Python to perform data validation, comparison, and profiling activities.
• Assist in identifying data inconsistencies and defects, and support root cause analysis (RCA).
• Support test execution, defect logging, tracking, and reporting activities.
• Participate in data pipeline validation to ensure accuracy, completeness, and consistency.
• Assist with documentation of test cases, results, and validation reports.
• Collaborate with data engineers, business analysts, and project teams to ensure quality deliverables.
• Support adherence to data governance, compliance, and quality standards in the BFSI domain.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
• Basic Understanding Of SQL and databases ETL/data warehousing concepts.
• Data validation and testing fundamentals.
• Exposure (academic/project Level) To Python (basic scripting for data tasks).
• Data analysis or reporting tools.
• Strong analytical, attention-to-detail, and problem-solving skills.
• Good communication and documentation skills.

Qualifications

• Unique Experience from this Role: Exposure to large-scale ETL/data pipeline testing in a banking environment.
• Opportunity to work on financial data systems and regulatory data validation.
• Hands-on experience in data quality assurance and testing practices.
• Collaboration with cross-functional teams, including data engineers and business stakeholders.
• Practical exposure to real-world data governance and compliance standards.

Skills

• Foundational knowledge in ETL/data testing and quality assurance.
• Hands-on experience with SQL and Python for data validation.
• Understanding of data pipelines, transformations, and warehousing concepts.
• Knowledge of defect tracking, root cause analysis, and test lifecycle processes.
• Knowledge of BFSI domain data systems and compliance requirements.
• Enhanced analytical thinking, attention to detail, and communication skills.

Benefits

• Opportunity to grow into roles such as Data QA Engineer, ETL Tester, or Data Engineer.