Senior Data Engineer – Insurance Data Platform

Overview

Senior Data Engineer – Insurance Data Platform

 

Location: RemoteSchedule: Monday – Friday, 8:00 AM – 4:30 PM CT (additional hours as needed)Salary Range: $100,000 – $150,000 (commensurate with experience)

 

Build Your Career With Purpose at CCMSI

 

At CCMSI, we partner with global clients to solve their most complex risk management challenges, delivering measurable results through advanced technology, collaborative problem-solving, and an unwavering commitment to their success.

 

We don’t just process claims—we support people. As the largest privately-owned Third Party Administrator (TPA), CCMSI delivers customized claim solutions that help our clients protect their employees, assets, and reputations. We are a certified Great Place to Work®, and our employee-owners are empowered to grow, collaborate, and make meaningful contributions every day.

 

Job Summary

The Senior Data Engineer has a firm grasp of insurance data and serves as the owner and designer of data pipelines which moves claims, policy, billing, medical, and financial data from our core administration systems into our analytics platform, and from there into client-facing reporting, internal dashboards, and ML models.

 

This is a builder role which architects, writes code, mentors junior engineers, and partners directly with claims operations, actuarial, finance, and CCMSI’s client services teams to transform operational data into usable format for decision making.

 

Accuracy, scalability, and reliability are critical—this data supports client reporting, regulatory filings, and financial decision-making.

 

Responsibilities

 

Design, build, and maintain ELT/ETL pipelines moving data from our claims administration system (iCE), policy admin, medical bill review, banking, and third-party vendor feeds into our cloud data warehouse.

 

Own the data models for core insurance objects — claims, policies, coverages, reserves, payments, recoveries, exposures, units, and loss development triangles — and make sure they hold up under actuarial scrutiny.

 

Build and maintain integrations with external vendors and partners — medical bill review (MBR), pharmacy benefit managers (PBM), bureau reporting (NCCI, state bureaus, ISO), excess carriers, and client BI environments.

 

Develop and support the data feeds that drive client loss runs, board reports, and self-insured trust deliverables.

 

Accuracy here is non-negotiable — these reports go to clients, auditors, and regulators.

Build and maintain data quality monitoring, anomaly detection, and reconciliation processes. If a paid loss number is wrong, we need to know before the client does.

 

Partner with the actuarial and analytics teams on loss development, IBNR, and trending data structures — including the triangle data that feeds reserve studies.

 

Support state and federal regulatory reporting data needs (EDI claims reporting, Medicare Section 111)

 

Qualifications

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skills, and/or abilities required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

 

Insurance Experience (Non-Negotiable)

 

• 5+ years working with insurance data in a carrier, TPA, MGA, broker, or insurance-tech environment.
• Deep working knowledge of claims data structures — claimants, coverages, reserves (indemnity, medical, expense), payments, recoveries, financial transactions, and the relationship between policy and claim.
• Experience with at least one major claims administration system
• Familiarity with workers' compensation and/or general liability claims data specifically — jurisdictional rules, body parts, ICD/CPT codes, NCCI class codes, etc.
• Comfortable with insurance financial concepts: paid vs incurred, case reserves vs IBNR, loss development, reinsurance recoveries, deductibles, SIRs, and aggregate stop-loss.

Technical

 

• 8+ years total professional data engineering experience.
• Expert SQL — window functions, recursive CTEs, query tuning, execution plans. You should be able to look at a slow query and know where it's going to hurt.
• Strong Python for data work (pandas, PySpark, SQLAlchemy, plus general-purpose Python — APIs, testing, packaging).
• Production experience with at least one modern cloud data warehouse (Snowflake, Databricks, BigQuery, Synapse,