Description :

About the Job

The DQM team manages the implementation of best-in-class data quality measurement programs for the US region within the retail consumer banking domain. The team supports several critical areas, including :

- Regulatory Support : Execution of business data quality measurements as required by regulatory programs such as CCAR and AML.

- DQ Rules Design : Identification of critical data elements across systems, designing data quality rules, and performing testing and validation.

- Data Governance : Standardization of data definitions and ensuring consistency in measurement across systems, products, and regions.

- DQ Scorecards : Publishing monthly/quarterly product-level scorecards and preparing executive summary reports for senior management.

- Issue Management : Identifying data defects, conducting root-cause analysis, and following up with stakeholders to ensure closure as per SLA.

- Audit Support : Identifying control gaps, tracking policy breaches, and providing data evidence for audit requirements.

Expertise Required :

Analytical Skills :

- Strong ability to perform data analysis and data visualization.

- Proficiency in formulating analytical methodologies, identifying trends, patterns, and correlations within datasets.

- Ability to generate actionable business insights.

Tools & Platforms :

- Proficient in SAS and SQL.

- Strong skills in MS Excel and PowerPoint.

Domain Skills :

- Good understanding of data definitions, data discovery, data quality frameworks, data governance, and data warehouse concepts.

- Preferred : Knowledge of financial regulations and familiarity with the retail banking business.

Technical Skills (Key Competencies) :

- Strong proficiency in SQL for data extraction, transformation, and validation

- Hands-on experience with SAS (Base + Macros)

- Expertise in Data Quality frameworks, rule design, and measurement

- Knowledge of Data Governance principles, data definitions, data lineage, and metadata

- Understanding of Data Discovery and data profiling techniques

- Familiarity with Data Warehousing concepts and ETL processes

- Proficiency in MS Excel (advanced), PowerPoint, and data visualization techniques

- Ability to perform trend analysis, data investigation, and root cause analysis

- Experience with data issue management, defect identification, and remediation tracking

- Knowledge of banking / retail banking domain and finance regulatory requirements (CCAR, AML preferred)

- Working knowledge of analytics tools such as Python or R (preferred, not mandatory)

- Experience using Power BI/Tableau for dashboards and reporting (preferred)

Education & Experience :

- B.Tech/B.E. in Information Technology, Information Systems, or Computer Applications.

- Preferred : Post-graduate qualification in Computer Science, Mathematics, Operations Research, Econometrics, Management Science, or related disciplines.

- 6 to 9 years of hands-on experience in delivering data quality solutions, with at least 1 year of experience in the banking industry.