Principal Data Engineer

Job Description

Applicants must be a resident and work from one of the following states: WA, OR, , TX, OH, IL, MN, NC, SC or FL, with occasional travel to our headquarters, located in Seattle, WA.

At PEMCO, we’re all about people – our customers, our employees, and the community. We’re a mutual insurance company owned by our Northwest policyholders. We provide auto, home, renters, and boat coverage. Recognized by Forbes as one of America’s Best Insurance Companies in both Auto and Home for 2026, based on customer survey feedback, and by Newsweek as one of America’s Greatest Midsize Workplaces 2025.

We are consistently recognized for our outstanding customer service, employee expertise, community partnerships, and social impact programs. All of which makes PEMCO a great place to work! Our social impact programs motivate high achievement by youth in education; build stronger and greener communities; and increase safety at home, on the road, and ’re committed to diversity, equity, inclusion, and belonging, and to fostering an inspiring and inclusive workplace.

These efforts create and cultivate an environment that builds fairness and understanding, encourages collaboration and flexibility, and celebrates all the ways in which we’re different and the same - enabling all individuals to achieve their full potential.

Applicants must be a resident and work from one of the following states: WA, OR, , TX, OH, IL, MN, NC, SC or FL, with occasional travel to our headquarters, located in Seattle, WA.

The Principal Data Engineer serves as PEMCO’s senior individual contributor in the Data & AI Organization and is responsible for designing, building, and evolving scalable data processing patterns and data products that power analytics, reporting, operational intelligence, and AI across the enterprise. The Principal Data Engineer combines deep technical expertise with insurance domain knowledge to deliver trusted, reusable, and governed data assets that support underwriting, claims, policy, customer, finance, and regulatory reporting needs.

This role drives technical excellence through hands‑on engineering, architectural leadership, mentorship, and influence without direct people management responsibilities.

• Design and develop scalable, secure, and resilient data processing patterns, frameworks, pipelines, and reusable data products supporting enterprise analytics, reporting, and AI initiatives.
• Build and optimize cloud‑native data solutions leveraging Databricks, Spark, Delta Lake, Azure Data Platform services, SQL Server, and modern lakehouse architectures.
• Design and implement batch, streaming, and near real‑time data processing frameworks capable of handling large‑scale enterprise data workloads.
• Develop trusted, governed, and reusable datasets at atomic grain that can be leveraged across analytics, operational reporting, and AI use cases.
• Partner with business stakeholders, analysts, data scientists, architects, and engineers to translate complex business requirements into scalable data solutions.
• Establish and promote engineering standards, architectural patterns, and best practices related to data modeling, performance optimization, testing, observability, and reliability.
• Design and implement robust data integration solutions across policy, claims, billing, customer, finance, actuarial, and third‑party insurance systems.
• Drive modernization of legacy data platforms and accelerate migration toward cloud‑native data architectures and engineering practices.
• Optimize data pipelines, storage, compute utilization, and query performance to improve scalability, reliability, and cost efficiency.
• Collaborate with Data Governance teams to implement…