Job Description

Roles & Responsibilities

Technical Collaboration (Technical Appreciation) ● Bridging Business and IT Translate business data requirements and governance policies into clear, actionable technical specifications for IT and Data Engineering teams. ● Data Lineage & Cataloging Work with data architects to map end-to-end data lineage (system-of-origin to system-of-consumption) and support the population of the Enterprise Data Catalog. ● Tooling Oversight Evaluate and maximize the ROI of technical data governance and data quality tools. Review outputs from data profiling and automated quality checks. ● Querying & Validation Perform lightweight data profiling and validation to verify data quality issues independently before escalating to engineering teams. Required Qualifications & Experience ata quality dashboards.

Desired Candidate Profile

● Domain Expertise: 8+ years of total experience, with a minimum of 4 years specifically in Data Governance, Data Stewardship, or Data Quality within the Banking and Financial Services sector. ● Subject Matter Expert: Deep understanding of banking products, processes, and regulatory reporting requirements (e.g., AML, KYC, Risk Management). ● Strategic Execution: Proven track record of drafting data policies, defining CDEs, and successfully establishing a network of data stewards. ● Communication: Exceptional stakeholder management skills, with the ability to translate complex technical constraints into business realities, and vice-versa. ● Certifications: Certifications such as CDMP (Certified Data Management Professional) or equivalent are highly preferred. Technical Skills & Appreciation ● Query Languages: Foundational ability to read and write SQL to query databases, perform basic data profiling, and validate data sets independently. ● Governance Tooling: Familiarity and hands-on conceptual knowledge of industry- standard enterprise tools such as Informatica (Axon, EDC, IDQ), Collibra, or Alation. ● Data Architecture Concepts: Strong conceptual understanding of Relational Databases, Data Warehousing, Data Lakes, and Cloud infrastructure (AWS/Azure) to effectively converse with technical architects. ● BI & Reporting: Appreciation for Business Intelligence tools (Power BI, Tableau) to design and interpret data quality dashboards.