Job Description
Job Description
Reinsurance Accounting & Risk Data Engineer (Data Fabric / Data Architecture)
Location: Boston, MA (Onsite 4 days/week)
About Our Client
Our client is a global investment firm building foundational AI, data, and platform capabilities that enable global scale and business transformation. Within that platform organization, an Insurance & Reinsurance Data Engineering function designs, governs, and enables the enterprise data architecture that powers reinsurance accounting, treaty management, risk analytics, and regulatory reporting.
The Role
Our client is hiring a Reinsurance Accounting & Risk Data Engineer to join a core AI/Data/Platform engineering group in Boston. This is a pivotal, hands-on technical leadership role requiring deep expertise in reinsurance accounting data, risk data architecture, data modeling, and modern Data Fabric design.
You will lead the design and strategic evolution of the enterprise data architecture supporting reinsurance accounting, treaty management, and risk analytics—ensuring seamless integration, reconciliation, and accessibility across ceded and assumed portfolios, counterparty risk systems, and financial reporting platforms.
You'll partner closely with reinsurance operations, actuarial, finance, risk management, and technology teams to ensure treaty structures, premiums, loss recoveries, reserves, collateral, exposures, and regulatory capital data are accurate, consistent, and usable for accounting close, compliance, analytics, and strategic decision-making.
Work model: onsite in Boston 4 days/week.
What You'll Do
- Design and implement a scalable Data Fabric enabling unified, real-time access to reinsurance accounting and risk data across distributed systems and domains
- Define and maintain enterprise data architecture vision, principles, standards, and reference architectures aligned to the firm's platform strategy
- Lead development of enterprise-grade conceptual/logical/physical data models for: treaty structures, ceded/assumed accounting, loss recoveries, collateral, counterparty risk, and regulatory capital
- Establish data modeling standards, naming conventions, and best practices to ensure consistency and reusability across the ecosystem
- Implement data governance frameworks, data quality standards, and stewardship processes aligned with key accounting/regulatory standards (STAT, GAAP, IFRS 17, LDTI, Solvency II, BSCR, RBC)
- Build foundational capabilities for data lineage, cataloging, metadata management, and reconciliation
- Partner with operations, treaty accounting, actuarial, finance, and risk teams to understand requirements and translate them into durable data architecture
- Enable risk aggregation, catastrophe modeling, counterparty exposure analytics, and data readiness for advanced analytics and AI/ML workloads
- Operate as a reinsurance domain expert advising on treaty terms, reserve methodologies, settlement flows, credit risk, retrocession, and regulatory capital impacts
- Provide technical leadership across modern data stack components including Snowflake, AWS (S3, Glue, Redshift), Databricks, and Azure Synapse
- Mentor junior architects/data engineers/analysts and raise the bar on architecture rigor and domain data standards
What Our Client Is Looking For
- Bachelor's or master's degree in CS/IS/Data Science/Actuarial/Finance/Math or related field
- 10+ years of experience in enterprise data architecture/modeling/management/engineering, with a strong focus on reinsurance accounting and/or insurance risk in financial services
- Proven experience designing Data Fabric (or similar enterprise integration architectures: Data Mesh, data virtualization, metadata-driven architectures) in an insurance/reinsurance context
- Deep reinsurance domain knowledge: treaty types (proportional, non-proportional, facultative, retrocession), ceded/assumed accounting, settlement processes, receivables/payables, collateral, loss recovery, counterparty credit risk
- Strong knowledge of reinsurance accounting standards/regulatory frameworks: STAT, GAAP, LDTI, Solvency II, BSCR, RBC
- Hands-on technical strength in SQL; ability to validate, reconcile, and troubleshoot complex data issues independently; Python preferred
- Experience with cloud data platforms (Snowflake, Redshift, Databricks, Azure Synapse) and data integration/ETL frameworks
- Strategic, automation-oriented mindset with strong stakeholder management and communication skills
Why This Role
- High-impact ownership of enterprise data architecture that powers accounting close, compliance, and risk decision-making
- Deep domain + technical work at the intersection of reinsurance operations, actuarial, finance, risk, and modern data platforms
- Opportunity to build a durable Data Fabric foundation that enables real-time insights and AI/ML-ready datasets