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Lead Data Analyst

About the role

A Leading insurance client is looking for a hands-on contractor to strengthen and modernise its investment data and reporting. The work centres on Clearwater Analytics: making sure investment data flows cleanly from source to subledger to general ledger to final report. You’ll find where the data breaks and fix the cause, and build repeatable, automated controls in place of manual effort.

What you’ll do

  • Own investment data quality in Clearwater, covering data validation, attribute and entity mappings, and the business rules that feed downstream finance reporting.
  • Design and run reconciliations from general ledger to investment subledger to report, and between other systems (for example IBOR, ABOR and SBOR). Investigate variances, find the root causes and resolve breaks before they reach the close.
  • Find and deliver process improvements and transformation work across the reporting cycle, including better data flows, fewer exceptions and less manual effort.
  • Build and improve reporting and data models in Power BI and SSAS, and explore AI and agent-based tools that make review and exception handling more efficient.
  • Research and resolve data and operational exceptions, including daily transaction processing issues, and fix the cause so the same break doesn’t come back.
  • Work with Finance, Investments, Operations, ALM, Risk, Technology and external service providers on recurring deliverables and change initiatives.

What you’ll bring

  • 3-5 years of hands-on Clearwater Analytics experience, ideally with data validation, reconciliations and reporting for an insurance investment portfolio.
  • A strong data background, including data mapping, transformation logic, data quality rules, lineage and reconciliation design across investment systems.
  • Proven experience automating or redesigning finance processes, such as building repeatable validation checks, cutting manual close effort or improving reporting workflows.
  • Advanced Excel skills. SQL or query experience is a strong plus.
  • Comfort working through ambiguity, prioritising issues and keeping recurring deliverables on schedule while you improve the process behind them.
  • Clear communication with both finance and technical stakeholders.

Nice to have

  • Power BI, SSAS or other data modelling and semantic layer experience
  • Exposure to AI or LLM-assisted workflows or agent tools
  • PeopleSoft General Ledger
  • Experience with IBOR platforms (for example Aladdin) alongside Clearwater