Mutual of Enumclaw Insurance Company seeks a Data Analytics Engineer to design, govern, and deliver analytics-ready data assets across the property and casualty value chain. This role emphasizes collaboration with stakeholders and advancing Snowflake based medallion architecture to support data-driven decision making.
Role Overview
The Data Analytics Engineer partners with cross-functional teams to translate business needs into scalable data solutions, building trusted dashboards and analytical products that empower underwriters, actuaries, claims leaders, distribution partners, and executives. The position supports both recurring and ad hoc reporting while maintaining rigorous data governance and quality standards.
Responsibilities
- Collaborate with stakeholders in Product, Actuarial, Underwriting, Claims, Finance, and Distribution to collect requirements, define KPIs, and specify data needs.
- Develop, deploy, and sustain dashboards, reports, and visualizations on Sigma, Power BI, or equivalent BI platforms to deliver trusted insights.
- Convert business needs into scalable data solutions, dashboards, and analyses that inform strategic and operational decisions.
- Support both recurring and ad hoc reporting, including financial, operational, and executive summaries.
- Design and maintain data models, transformations, and semantic layers within a Snowflake based medallion architecture.
- Build scalable, testable data pipelines using SQL and dbt or equivalent tooling.
- Ingest data from internal and external sources such as policy systems, Salesforce, and HubSpot.
- Enable self-service analytics by provisioning semantic layers and certified data products for business users.
- Define and enforce data governance standards, including data definitions, access controls, and metadata management.
- Validate data outputs to ensure accuracy and reliability, and monitor data performance for continuous improvement.
- Collaborate with Product Owners and participate in Agile ceremonies including planning, refinement, and sprint reviews.
- Define acceptance criteria and deliver high quality data products.
- Provide production support and troubleshoot data or reporting issues as needed.
Requirements
- P&C insurance industry experience required, with understanding of the insurance value chain from underwriting to claims and fluency in core concepts, terminology, and reporting metrics.
- Proven ability to design, build, and publish dashboards and reports in Sigma, Power BI, or equivalent BI platforms, including data modeling for self-service consumption.
- Extensive experience with cloud data warehouses (Snowflake preferred) and transformation tools such as dbt.
- Proficiency in SQL; working knowledge of Python or similar scripting languages is preferred.
- Solid understanding of dimensional modeling, ELT processes, and modern data architectures such as medallion or lakehouse.
- Experience building or migrating to a modern data platform (for example, moving from legacy data warehouses to Snowflake/medallion architecture) is preferred.
- Knowledge of data integration methods (APIs, flat files, semi-structured data) and cloud platforms (AWS or equivalent).
- Strong communication skills with the ability to translate technical concepts for business audiences.
- Experience working in Agile environments.
Technologies
- Snowflake
- dbt
- Sigma
- Power BI
- SQL
- Python
- Salesforce
- HubSpot
- Guidewire
- PolicyCenter
- ClaimCenter
- BillingCenter
- POINT
- Duck Creek
- AWS
Location and Work Arrangement
Remote position with a preference for candidates residing in Washington, Oregon, Idaho, Montana, Wyoming, Arizona, or Utah. Candidates must be able to work during core Pacific Standard Time hours and have high-speed internet; an internet speed test is required.
Salary
Annual compensation range: USD 140,891 to USD 171,631.
Education
Bachelor’s degree in data science, computer science, statistics, or a related field, or equivalent experience.
Experience
Minimum of 5 years of relevant experience.
Supervisory Responsibilities
None.
Physical Requirements
Prolonged periods of sitting at a desk and working on a computer, including video conferencing.
