Who We Are:
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 2025 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 at play. We’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.
Why We Need You:
The Senior Databricks AI/ML Engineer focuses on building and deploying scalable AI/ML solutions across key areas of the insurance functions, including underwriting, claims, pricing, customer engagement, and fraud detection, with a strong emphasis on Databricks architecture and ecosystem integration. The engineer will collaborate closely with data scientists, actuaries, product owners, and engineers to operationalize models, transforming them into robust, production-grade systems seamlessly integrated into business workflows and enterprise platforms.
What You’ll Be Doing:
• Conduct customer workshops to identify requirements and provide architecture design for analytics projects with Azure and Databricks AI/ML products & services.
• Serve as Databricks Architect responsible for designing, deploying, and governing Databricks workspaces and resources across multiple environments (Dev, Test, Prod).
• Define and implement Databricks Lakehouse architecture, set up best practices for Databricks governance and integrate Databricks with Azure services
• Lead implementation of Databricks SQL, Delta Live Tables, and MLflow tracking for reproducible and scalable experimentation.
• Develop and maintain automated MLOps workflows for model deployment and monitoring
• Set up and configure Azure and Databricks AI/ML products and infrastructure.
• Conduct code review for ML models and other code related to smart analytics, AI & ML
• Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics and business conduct.
• Authentically support the PEMCO Brand and constantly are on the lookout for top talent to join us to achieve our Mission to Worry Less and Live More.
• Other duties as assigned.
• Design and develop data pipelines, and cloud services for monitoring, analysis and reporting.
• Build and maintain robust ETL workflows using Databricks, Spark, and SQL Server to ingest, clean, transform, and load structured and unstructured data.
• Provide production support and monitoring for data engineering workflows, including incident resolution and performance tuning.
• Develop and optimize complex SQL queries and stored procedures in SQL Server for data processing, validation, and business rule implementation.
• Partner with cross-function team members to design the data collection spec and process and ensure trustworthiness of data to enable and improve reliability, scalability, and efficiency of critical business decisions.
• Define, deploy, and optimize algorithms to enable machines to identify patterns in programming data for business defined use cases.
• Scale data scientist models to handle terabytes of data.
• Feed raw data gathered from pipelines into models defined by data scientists.
• Build deployment pipelines for new models.
• Establish scalable MLOps practices to streamline model lifecycle management
• Implement logging and observability for AI/ML performance.
• Conduct architecture design review and performance tuning and testing.
What You'll Bring:
• B.A./B.S. degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science or Data Engineering or a related field or equivalent work experience is required.
• Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science or Data Engineering or a related field preferred.
• 6+ years of hands-on experience building ETL pipelines, managing production data workflows, and developing SQL in SQL Server environments.
• 3+ years of enterprise scale experience in using Azure and Databricks AI/ML products & services, including experience with complex data analysis techniques and visual analytics.
• 3+ years of enterprise scale experience in solving business problems using Azure and Databricks AI/ML services in combination with building data pipelines, data streams, and system integration.
• 3+ years of enterprise scale experience in transforming data science prototypes and applying appropriate ML algorithms and tools.
• 5+ years of enterprise scale experience with CI/CD and Development workflows for ML models and related code/scripts/apps.
• Experience in the insurance industry and understanding of Auto, Home, and Umbrella insurance-related AI/ML applications.
• Expertise in building and maintaining batch and streaming data pipelines for real-time and offline analytics.
• Experience with unsupervised learning techniques to identify patterns and anomalies in data.
• Familiarity with agile software delivery methodologies such as Scrum.
• Familiarity with platforms and enabling tools such as Azure Machine Learning, Azure Databricks, Microsoft Fabric, Synapse Analytics, Power BI, Snowflake, and APIs like Azure OpenAI, Azure Cognitive Services, and Azure ML Endpoints
• Strong knowledge of real-time data streaming frameworks like Apache Kafka, Azure Event Hubs, and Delta Live Tables for Databricks
• Engineering skills in AI/ML at enterprise scale to develop frameworks for analytic solutions to business goals.
• Hands-on experience with implementing AI/ML solutions that enable data-driven decision making and insights.
• Strong Math and problem-solving skills.
• Ability to learn new skills rapidly and apply as needed, e.g., learn a new machine learning algorithm from a research paper and implement it.
• Detail oriented with strong organizational, analytical, and communication skills.
• Service minded with experience deciphering ambiguous requests and taking ownership.
• Ability to create and maintain positive relationships with employees at all levels of the organization.
• Ability to work independently and manage tasks with minimal supervision.
Compensation:
The pay range for this role is shown below. Compensation decisions are determined based on an individual’s qualifications, job-related knowledge, skills, and experience.
• Greater Seattle area target pay range: $150,334-$183,742. The full pay range is $125,279-$208,798.
• Outside greater Seattle area target pay range: $132,673-$162,155. The full pay range is $110,561-$184,268.
Greater Seattle Area is defined as working within approximately 100 miles of Seattle.
Outside Greater Seattle is defined as working approximately 100 miles or more from Seattle.
Benefits:
Regular part-time PEMCO employees working at least 24 hours per week and regular full-time PEMCO employees are eligible to elect coverage under medical, dental, and vision plans for themselves and their eligible family members with generous employer premium cost shares. In addition, as a benefits-eligible employee, you are:
• covered by employer-paid basic life and accidental death & dismemberment insurance policies as well as long- and short-term disability benefit coverages.
• eligible to participate in PEMCO’s 401(k) plan which includes a generous employer match (2 for 1 on the first 6% employee pre-tax and/or Roth deferral, up to federal maximums).
PEMCO provides the following paid leave programs for benefits-eligible employees in their first year of PEMCO employment:
• Vacation accrues at a rate of 10 days for new hires, and increases based on a schedule to a maximum annual accrual of 25 days based on tenure.
• Granted four (4) personal days immediately upon hire.
• Paid holidays for the eight (8) holidays observed by PEMCO throughout the calendar year.
• Granted up to ten (10) days of sick leave immediately upon hire (pro-rated based on hire date and full-time/part-time status), which is approximately 28 hours more per year than the Washington state-required accrual.
• In addition, PEMCO provides paid time off for bereavement, jury duty, and employee volunteering in the community.
Other miscellaneous benefit programs offered by PEMCO include:
• Flexible Spending Accounts.
• Education Assistance Program after one year of service.
• Scholarship program for children of PEMCO employees after one year of service.
• Employee Assistance Program.
• Well-being program.
• Discretionary taxable gifts and gift cards.
• And other Perks & Benefits including discounts on computer software and hardware, cell phone plans, and rental cars.
Other compensation depending on role, contributions, and performance may include:
• Discretionary bonuses.
• Tiered sales commissions and/or incentives (from 5-25% of employee’s monthly sales).
• Employee referral bonuses.
• Shift differential pay.
Equal Employment Opportunity:
At PEMCO, we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our products, and our community to flourish. PEMCO is honored to be an equal opportunity workplace. We are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national orientation, age, citizenship, marital status, disability, gender identity, sexual orientation, or veteran status.
Applicants have rights under Federal Employment Laws:
• Family and Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)
The Senior Databricks AI/ML Engineer focuses on building and deploying scalable AI/ML solutions across key areas of the insurance functions, including underwriting, claims, pricing, customer engagement, and fraud detection, with a strong emphasis on Databricks architecture and ecosystem integration. The engineer will collaborate closely with data scientists, actuaries, product owners, and engineers to operationalize models, transforming them into robust, production-grade systems seamlessly integrated into business workflows and enterprise platforms.