Data Quality Analyst

About the role

The Data Quality Analyst will help monitor, assess, and strengthen enterprise-wide data quality at the bank. The position is centered on running quality validations, spotting data issues, and supporting corrective action so that data remains dependable for analytics, regulatory reporting, and AI-related work. The role also contributes to building stronger data ownership and trust across business and technology teams.

Key responsibilities

• Run predefined data quality validations and checks against agreed rules and thresholds.
• Review and profile data, then compare records across source systems and downstream datasets to spot mismatches.
• Detect issues affecting accuracy, completeness, consistency, timeliness, and validity of data.
• Help record, monitor, and close data quality incidents with guidance from senior colleagues.
• Assist with root cause investigations by studying data trends, exceptions, and unusual patterns.
• Coordinate with data engineering teams to understand pipelines, transformations, and movement of data.
• Contribute to the creation of dashboards, reports, and scorecards related to data quality.
• Keep documentation current for quality rules, identified issues, and resolution actions.
• Work in line with established standards, SOPs, and governance procedures for data quality.
• Support audits, internal assessments, and regulatory information requests when needed.

Qualifications and experience

A bachelor’s degree in Engineering, Statistics, Mathematics, Computer Science, or a similar discipline is required. The role calls for 1.5 to 6 years of experience in data analysis, data quality, or a closely related function. Experience with enterprise data environments is preferred, and prior exposure to banking or financial services will be an added advantage.

Technical skills

The ideal candidate should be comfortable using SQL and Python for data analysis and validation. A solid understanding of data quality dimensions and testing methods is needed, along with basic knowledge of data warehousing and ETL/ELT concepts. The role also requires the ability to reconcile data, identify anomalies, document findings, and report on quality metrics. Familiarity with data protection, access controls, and compliance expectations is important. Willingness to learn banking data domains and regulatory requirements is essential, and some exposure to analytics or AI data needs will be beneficial.

Additional information

This is a full-time onsite position based in Bengaluru, Karnataka, India.