Senior Data Engineer

MGT Insurance•Denver, CO

7d•Hybrid

About The Position

MGT Insurance is hiring a Senior Data Engineer to own end-to-end data pipelines for its cloud data warehouse. The role covers ingestion from policy administration systems, transformation and modeling of insurance data, and delivery of governed tables used by Finance, Actuarial, Underwriting, and Reinsurance. It sits at the integration layer connecting policy administration systems, rating engines, and third-party sources into a trusted warehouse that supports company reporting. The engineer is responsible for validating their own models and proving that reported figures reconcile to authoritative sources. The position offers autonomy over warehouse evolution and direct visibility with business leaders. The ideal candidate has experience with agentic-driven workflows, production data pipelines, SQL transformation frameworks, Python-based tooling and integrations, and rigorous testing practices. The role is hybrid, with a minimum of three office days per week; Denver, Madison, or San Francisco are preferred locations.

Requirements

Experience with agentic-driven workflows and development.
Several years of experience building production data pipelines, with strong SQL skills.
Experience with a cloud data warehouse and a SQL transformation framework such as Dataform, dbt, or an equivalent.
Python experience for data tooling and integrations, with comfort using APIs and semi-structured data.
Experience with git-based workflows, including branches, pull requests, code review, and CI.
Rigor about correctness, including testing one's own work and proving that a number is right.
An entrepreneurial mindset and ability to work independently and drive projects to completion.
Comfort working in a fast-paced environment where priorities change frequently.

Nice To Haves

P&C insurance domain knowledge, particularly around premium and policy lifecycle.
Experience with a policy administration system such as Socotra, including reporting across legacy and modern platforms simultaneously.
Workflow orchestration and cloud platform fundamentals; Airflow is preferred.
BI or semantic layer experience; Looker is preferred.
Post-M&A or cross-vendor data integration experience.

Responsibilities

Design, build, and maintain SQL transformation models from raw ingestion through the reporting layer.
Maintain and extend ingestion services that pull from source systems, ensuring they run reliably in production.
Monitor and manage warehouse cost, performance, and reliability.
Model insurance data, including policy lifecycle, premium, coverages, limits, and exposure, at the grain required for business reporting.
Document data definitions, business logic, and the reasoning behind data-modeling decisions.
Build agentic data quality controls alongside every model and ensure they detect regressions.
Reconcile work against authoritative sources and explain variances.
Work with Finance, Actuarial, Underwriting, and Product to turn ambiguous requests into reliable, repeatable data products.
Support the BI layer and analysts who use the data.