Senior Data Business Analyst
A well established reinsurance organisation is investing in its permanent internal data capability to meet growing demand across underwriting, operations, and finance. This is a senior, high impact role where you will help shape how data is defined, governed, and used across the enterprise.
You’ll sit at the intersection of business analysis, data architecture, and enterprise change, working closely with senior stakeholders, data architects, and engineering teams to turn complex data challenges into clear, governed, and scalable outcomes.
This role is ideal for a Senior Data Business Analyst who enjoys operating in a structured, regulated environment, influencing how data works at an organisational level rather than delivering reports in isolation.
What you’ll be doing
Leading Data Led Change
- Lead the initiation, discovery, and delivery of data focused initiatives across multiple business domains.
- Apply structured business analysis and change management approaches within a governance led delivery environment.
- Take ownership of smaller data projects and enhancements from early discovery through to business as usual adoption.
- Contribute to the ongoing evolution of data BA standards, tooling, and ways of working across the organisation.
Data Architecture Aware Business Analysis
- Capture and define requirements with a data architecture mindset, ensuring solutions are scalable, consistent, and fit for purpose.
- Work confidently with:
- Conceptual, logical, and physical data models
- Data warehousing and analytical data platforms
- The distinction between data dictionaries and data glossaries
- Master data vs reference data
- Define requirements using data flows, lineage, source to target mappings, and reporting specifications.
- Act as a critical bridge between business stakeholders and Data Architecture / Engineering teams, ensuring shared understanding and alignment.
This role contributes to data architecture through high quality requirements, rather than owning solution design.
Data Governance & Data Quality
- Embed data governance principles into delivery, including data ownership, standards, and controls.
- Support data quality assessments, issue identification, and remediation definition.
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