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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Databricks Ai/Ml Engineer - **Company:** PEMCO MUTUAL INSURANCE COMPANY - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $150,334.0 - $183,742.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Microsoft Azure, Code Review, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Transformation, Decision Support Systems, Fraud Prevention and Detection, Machine Learning, Microsoft SQL Server, Operational Databases, Performance Tuning, Scrum Methodology, Raw Data, Power BI, OpenAI, Cloud Services, Azure Machine Learning, Software Deployment, Software Engineering, SQL Stored Procedures, SQL Databases, Data Streaming, Systems Integration, Unstructured Data, Visual Analytics, Data Logging, Data Processing, Freeform SQL, Snowflake, Apache Spark, Microsoft Fabric, Information Technology, Apache Kafka, Machine Learning Operations, Stream Processing, Azure Synapse Analytics, Data Pipelines, Unsupervised Learning, Databricks - **Published:** November 7, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-databricks-ai-ml-engineer-seattle-wa--cbadb4bb-04c0-4a77-8bb2-e7992473d76e ## About the Role Artificial Intelligence (AI), Market Surveys, Insurance, Customer Support/Service, Automotive Industry, Diversity, Underwriting, Actuarial Skills, Artificial Intelligence (AI), Data Science, * 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. ## Description 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.