Senior Data Engineer

MGT Insurance•Denver, CO

11h•$150,000 - $200,000•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 integrates policy administration systems, rating engines, and third-party sources, transforming raw data into governed reporting tables used by Finance, Actuarial, Underwriting, and Reinsurance. The engineer will have autonomy over warehouse evolution and direct visibility with business leaders who rely on the data. The person who builds each model is also responsible for validating that it ties out to authoritative sources. The position focuses on developing reliable ingestion services and SQL transformation models, modeling insurance data, creating automated data quality controls, and partnering with business and product teams to develop repeatable data products. It also supports the BI layer and analysts who build on the warehouse. MGT describes a governed workflow in which models include their tests, pull requests are small and clean, and technical knowledge is documented in the repository. The role is hybrid, with a minimum of three days per week in the office. Denver, Colorado; Madison, Wisconsin; and San Francisco, California are preferred locations. The base salary range is $150,000–$200,000 annually, depending on qualifications, experience, and location. The position is also eligible for a performance-based bonus and equity, in addition to a comprehensive benefits package.

Requirements

Experience with agentic-driven workflows and development.
Several years of experience building production data pipelines.
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 a git-based workflow, including branches, pull requests, code review, and CI.
Strong commitment to correctness, including testing one's own work and proving that reported numbers are accurate.
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 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 data from source systems, ensuring they run reliably in production.
Monitor warehouse cost, performance, and reliability.
Model insurance data—including policy lifecycle, premium, coverages, limits, and exposure—at the grain needed for business reporting.
Document data definitions, business logic, and modeling decisions.
Build agentic data quality controls alongside every model and ensure they can detect regressions.
Reconcile data models against authoritative sources and explain variances.
Partner with Finance, Actuarial, Underwriting, and Product to turn ambiguous requests into reliable, repeatable data products.
Support the BI layer and analysts who build on the engineer's work.