Senior Data Quality and Governance Analyst – Assistant Vice President

Maintain Data Catalog/Dictionary: Document and maintain business, technical, and operational metadata, including data lineage, definitions, and data standards.

Data Lineage Mapping: Utilize metadata to map data lineage, understanding how data flows from source systems to downstream reporting to identify potential impact areas.

Policy Compliance: Ensure all data assets adhere to defined data governance policies and data privacy regulations.

Profiling Execution: Perform deep profiling of large datasets to understand data structure, patterns, and content, identifying hidden anomalies or missing information.

Root Cause Analysis (RCA): Investigate data quality issues to determine the root cause, distinguishing between upstream processing errors and data entry errors.

Data Assessment: Evaluate critical data elements (CDEs) for accuracy and completeness.

Rule Definition: Collaborate with business stakeholders to define and validate business rules for data validation (e.g., completeness, accuracy, consistency, validity).

Rule Authoring/Implementation: Develop and implement data quality rules, checks, and preventative/detective controls using SQL, Python, or specialized DQ tools.

Validation Logic: Document validation logic and exception-handling procedures for critical datasets.

Continuous Monitoring: Actively monitor data pipelines, ETL processes, and dashboards to proactively identify DQ issues and operational anomalies.

DQ Dashboards/Scorecards: Develop and maintain data quality metrics and scorecards to report on data accuracy trends to leadership.

Alerting: Set up automated alerts for breach of data quality thresholds.

Issue Resolution: Identify, document, and triage data quality issues through a tracking system.

Remediation Action Plans: Develop and execute remediation plans, including data cleansing efforts and automated corrections.

Cross-Functional Collaboration: Partner with data stewards, IT, and developers to resolve data issues and implement long-term solutions. (Preferred) –

MBA / Masters Degree in Economics / Statistics / Mathematics / Information Technology / Computer Applications / Engineering from a premier institute. BTech / B.E in Information Technology / Information Systems / Computer Applications

(Preferred) Post Graduate in – Computer Science, Mathematics, Operations Research, Econometrics, Management Science and related fields

10+ years of hands-on experience in people management, delivering data quality, MIS, data management with at least 2-3 years’ experience in Banking Industry

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