Finance Data Transformation Lead

Job description:          

Role Summary

• We are starting discovery for a finance data modernization at a leading global PC reinsurer The hub will consolidate finance actuarial claims policy and reinsurance data from multiple source systems into a governed financial data layer that feeds management and regulatory reporting FPA and in time conversational analytics We are looking for a functional lead who speaks both finance and data

What You Will Do:

• Lead discovery workshops with Finance Actuarial Reinsurance FPA and IT stakeholders to document the ASIS reporting and data landscape
• Inventory source systems GLERP EPM policy admin claims actuarial reserving ceded reinsurance investments and assess data availability grain quality and ownership
• Build the KPI and report inventory business definitions calculation logic dimensions named business owners and signoff
• Define critical data elements and map KPIs to source and target fields across a medallion architecture Bronze Silver Gold Semantic
• Shape the TOBE architecture with data architects financial data layer semantic layer reporting and self-service layer
• Write the BRD functional specifications assumptions and risks log and the phased roadmap
• Act as functional product owner for the Gold and Semantic layers as the engagement moves into build including UAT and self-service testing with business users
• Contribute to estimates SOW inputs and follow-on proposals

What You Bring Required:

• 37 years in finance transformation finance data or FPAcontrollership within insurance or reinsurance in consulting or industry
• Professional qualification CA CPA ACCA CFA or MBA Finance or equivalent depth
• Working fluency in PC reinsurance finance GWPNW Pearned premium UPR paid case IBNR and incurred losses ALAEULAE CAT vs nonCAT commissions and brokerage DAC lossexpensecombined ratios ceded reinsurance technical result
• Knowledge of at least one insurance reporting basis US GAAP US STATNAIC IFRS 17 or Solvency II and the bridges between them
• Hands-on experience with data modeling concepts star schemas conformed dimensions medallionLakehouse layers semantic models sourcetotarget mapping
• SQL proficiency sufficient to profile data and validate KPI logic independently
• Proven ability to run stakeholder workshops and produce client ready BRDs KPI catalogs and architecture narratives