Data Analyst

We are seeking a highly experienced Data Analyst to support the discovery, requirements, and design of an Enterprise Knowledge Hub. This role focuses on assessing complex data assets, defining semantic models, and supporting the development of knowledge graphs to enhance retrieval and AI-driven workflows. You will bridge the gap between technical data architecture and business requirements to ensure the success of enterprise-wide knowledge management initiatives.

Our client is a leading global provider of high-end research and analytics services, supporting major commercial and investment banks, insurance companies, and asset management firms. With a significant international presence, they deliver deep expertise in financial modeling, risk management, and business intelligence to global organizations. They are committed to driving innovation through advanced data strategies and cutting-edge technology solutions.

Responsibilities

• Identify and catalogue enterprise data and knowledge sources, including owners, domains, and refresh requirements.
• Assess structured data, metadata, taxonomies, and knowledge graphs to identify reusable assets and gaps.
• Collaborate with data teams to define business concepts, entities, relationships, and ontology requirements.
• Facilitate requirements gathering and translate discovery findings into functional, data, and non-functional requirements.
• Maintain comprehensive documentation including BRDs, RTMs, user stories, and measurable acceptance criteria.
• Evaluate platform options and enterprise services against requirements for search, security, and integration.
• Define governance requirements covering ownership, stewardship, classification, privacy, and lineage.
• Prepare workshop materials, capability maps, and stakeholder recommendations to drive project alignment.

Requirements

• 12 to 15 years of experience as a Data Analyst or Data Management Analyst in a complex enterprise environment.
• Strong expertise in data discovery, profiling, source inventory, and data-flow documentation.
• Deep understanding of metadata, taxonomy, ontology, semantic modeling, and knowledge-graph analysis.
• Proven experience in data governance, classification, quality, privacy, and auditability.
• Working knowledge of RAG, vector search, semantic search, AI grounding, and agentic AI concepts.
• Experience maintaining BRDs, RTMs, user stories, and delivery backlogs.
• Strong analytical, facilitation, and stakeholder management skills with the ability to communicate with executive leadership.
• Relevant bachelor degree; professional qualification preferred.
• Prior experience in banking or financial services is highly preferred.