Data Governance

apartmentVirtusa placeDubai calendar_month 

Job Description

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
  • 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.
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