Data Management Consultant

Overview

As a Data Management Consultant, you will help financial institutions design trusted, scalable data ecosystems and guide data-driven transformation. You’ll blend strategic advisory with hands-on delivery within Capco’s Data Strategy & Advisory practice, collaborating with cross-functional teams to implement AI-enabled data management capabilities. The role focuses on governance, quality, metadata, and AI-ready data while shaping target architectures and adoption across business and technology stakeholders. This is a hands-on, impact-driven opportunity at a global data practice.

Pay / Benefits

• Discretionary bonus
• pension
• health insurance
• life insurance
• mental health support
• parential leave and paid life events

Responsibilities

• Design and implement AI-enabled data management frameworks, including AI use cases and requirements; orchestrate workflows and configure AI-driven data management agents
• Define standards for metadata, data taxonomies, data products and semantic layers to support humans and models
• Collaborate with architecture and engineering to design target state architectures enabling AI data management
• Establish guardrails and governance for safe AI use in Data Management
• Define and embed data governance, ownership, and operating models aligned to business and regulatory objectives
• Deliver core data management capabilities (data quality, metadata, lineage)
• Support rollout and adoption of data management frameworks across business and technology stakeholders
• Contribute to Capco thought leadership on agentic and automated data management in financial services

Key requirements

• Strong experience in data management, data quality or data strategy
• Experience in Financial Services data teams
• Practical knowledge of DAMA, DCAM or CDMC governance frameworks
• Experience designing data management capabilities including DQ, lineage and metadata management
• Familiarity with Collibra, Solidatus, Ataccama or Informatica
• Clear communication with diverse stakeholders
• Strong stakeholder management with ability to drive adoption
• Understanding of modern data and AI platforms
• Ability to bridge data management and architecture to translate business problems into AI solutions

• clear communication
• stakeholder management
• ability to translate complex concepts for diverse audiences
• data governance
• data quality
• metadata management

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