Reinsurance Data Engineer

Careers at KKR • Boston, MA

4h • Onsite

About The Position

KKR is a leading global investment firm offering alternative asset management, capital markets, and insurance solutions, aiming for attractive investment returns through a patient and disciplined approach. KKR's ADAPT (AI, Data and Platform Technologies) Engineering team is crucial to the firm's technological strategy, building and supporting foundational data and AI capabilities to drive global scale and business transformation. The Insurance & Reinsurance Data Engineering function within ADAPT is responsible for designing, governing, and enabling the enterprise data architecture for KKR's reinsurance accounting, treaty management, risk analytics, and regulatory reporting. KKR is seeking a Reinsurance Accounting & Risk Data Engineer for the ADAPT Engineering team 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. The successful candidate will lead the design and strategic evolution of the enterprise data architecture supporting KKR's reinsurance accounting, treaty management, and risk analytics functions, ensuring seamless integration, reconciliation, and accessibility across various platforms. This individual will partner with reinsurance operations, actuarial, finance, risk management, and technology teams to ensure data accuracy, consistency, and effective leverage for accounting, compliance, risk analytics, and decision-making. The role involves defining the technical blueprint for structuring, storing, and leveraging reinsurance and risk data to power KKR's insurance platforms, ensuring data integrity, performance, and accessibility. This is an onsite role, with expectations to be in our Boston offices 4 days per week.

Requirements

• Bachelor's or master's degree in Computer Science, Information Systems, Data Science, Actuarial Science, Finance, Mathematics, or a related field.
• 10+ years of relevant professional experience in enterprise data architecture, data modeling, data management or data engineering with a strong focus on reinsurance accounting and/or insurance risk management within the insurance or financial services industry.
• Proven experience designing and implementing Data Fabric or similar enterprise data integration architectures (Data Mesh, data virtualization, metadata-driven architectures) in a reinsurance or insurance context.
• Strong understanding of the reinsurance domain including treaty types (proportional, non-proportional, facultative, retrocession), ceded/assumed accounting, settlement processes, reinsurance receivables/payables, collateral management, loss recovery and accounting and counterparty credit risk.
• Deep knowledge of reinsurance accounting standards and regulatory frameworks including STAT, GAAP, LDTI, Solvency II, BSCR, RBC.
• Hands-on technical expertise with SQL and data querying/analysis to explore, validate, reconcile and troubleshoot reinsurance data issues independently.
• Experience with modern cloud data platforms (e.g., Snowflake, AWS Redshift, Databricks, Azure Synapse) and data integration/ETL frameworks.
• A strategic technical mindset focused on automation, continuous improvement and delivering measurable business outcomes in a dynamic, fast-paced environment with complex multi-entity reinsurance structures.
• Excellent communication, stakeholder management and the ability to translate complex reinsurance and risk data concepts for diverse audiences including senior leadership.

Nice To Haves

• Proficiency in Python or equivalent programming language preferred.

Responsibilities

• Design and implement a scalable Data Fabric architecture enabling unified, real-time access to reinsurance accounting and risk data across distributed systems and business domains.
• Define and maintain enterprise data architecture vision, principles, standards and reference architectures for the reinsurance data ecosystem aligned with KKR's ADAPT strategy.
• Lead development of enterprise-grade conceptual, logical and physical data models for treaty structures, ceded/assumed accounting, loss recoveries, collateral, counterparty risk and regulatory capital.
• Establish and enforce data modeling standards, naming conventions and best practices ensuring consistency, reusability and scalability across all reinsurance and risk data assets.
• Implement robust data governance frameworks, data quality standards and stewardship processes ensuring compliance with STAT, GAAP, IFRS 17, LDTI, Solvency II, BSCR and RBC requirements.
• Establish data lineage, cataloging, metadata management and reconciliation frameworks as foundational components of the reinsurance Data Fabric architecture.
• Partner with Reinsurance Operations, Treaty Accounting, Actuarial, Finance and Risk teams to understand data needs and strategic use cases across the reinsurance lifecycle.
• Enable risk aggregation, catastrophe modeling, counterparty exposure analytics and ensure data readiness for advanced analytics and AI/ML workloads.
• Act as a reinsurance domain expert advising on treaty terms, ceded/assumed accounting, reserve methodologies, counterparty credit risk, retrocession and regulatory capital impact.
• Provide technical leadership across the modern data stack including Snowflake, AWS (S3, Glue, Redshift), Databricks and Azure Synapse for reinsurance data solutions.
• Mentor and guide junior architects, data engineers and analysts on reinsurance data architecture best practices, data modeling standards and domain knowledge.

Benefits

• Employees may be eligible for a discretionary bonus, based on factors such as individual and team performance.
• KKR is an equal opportunity employer.
• KKR will provide reasonable accommodations as required by applicable federal, state, and/or local laws.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 501-1,000 employees