Overview

We are seeking a Senior Business Analyst / Data Modeler to serve as the key liaison between business stakeholders and the data engineering team. The role focuses on translating complex business and regulatory requirements into structured data models, supporting data mapping, and ensuring that validation logic accurately reflects business processes and compliance needs. Client: Our client is a global investment organization managing significant capital with a focus on long‑term value creation. The firm invests across key sectors including technology, healthcare, consumer, and financial services, combining deep sector expertise with a collaborative approach to support companies at every stage of growth. Project Overview: The client is undergoing a migration from one financial services technology platform to another. The project aims to ensure a smooth, accurate, and controlled transition across all stages, requiring detailed business rule definition, data modeling, and validation logic to maintain consistency and compliance throughout the migration process.

Responsibilities:
  • Gather, analyze, and document business and data requirements across multiple stakeholders.
  • Define, maintain, and optimize data models to support validation, reconciliation, and reporting processes.
  • Translate business rules and regulatory requirements into clear acceptance criteria.
  • Develop data models representing core business concepts and operational flows.
  • Support data mapping activities between legacy systems, the new platform, and validation datasets.
  • Act as the primary point of communication between business teams and data engineering.
  • Ensure clarity, consistency, and alignment in requirements throughout the project lifecycle.
Required Qualifications:
  • Strong experience as a Senior Business Analyst and/or Data Modeler in data‑driven or migration‑focused projects.
  • Background in asset management, ideally with experience in private equity.
  • Proven ability to take ownership of requirements and deliver clarity, completeness, and traceability.
  • Strong understanding of end‑to‑end investment and financial processes and how they translate into technical workflows.
  • Solid knowledge of data modeling concepts, including conceptual, logical, and physical data structures.
  • Hands‑on experience with data validation, reconciliation, and data quality frameworks.
  • Expertise in translating business needs into operational and software requirements, performing analysis, and proposing actionable solutions.
  • Excellent communication skills, with the ability to influence stakeholders and facilitate workshops.
  • Experience working in Agile or hybrid delivery environments.
Note:

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