Principal Data Engineer

PEMCO • Seattle, WA

6d • Remote

About The Position

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.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related technical field is required.
• 10+ years of experience in Data Engineering, Data Warehousing, Big Data Engineering, or related disciplines is required.
• 5+ years of experience designing and implementing cloud-based data solutions on Azure or equivalent cloud platforms is required.
• Proven experience building and operating enterprise-scale data platforms supporting high-volume analytics and operational workloads is required.
• Extensive experience with Databricks, Apache Spark, Delta Lake, PySpark, and lakehouse architectures is required.
• Strong experience with SQL Server, T-SQL, database engineering, performance tuning, and large-scale data processing is required.
• Experience designing dimensional models, Data Vault models, or other modern data product architectures is required.
• Expert-level proficiency in SQL, data modeling, database design, and large-scale data engineering is required.
• Advanced proficiency with Databricks, Spark, Delta Lake, and distributed data processing frameworks is required.
• Demonstrated expertise designing scalable ELT/ETL solutions and modern data architectures is required.
• Strong understanding of cloud-native architecture patterns, data platform design, and analytics engineering is required.
• Experience designing highly reusable and governed data products that support reporting, analytics, and AI workloads is required.
• Demonstrated knowledge of data quality, lineage, metadata management, observability, and operational monitoring is required.
• Strong understanding of data governance, security, privacy, and regulatory compliance controls is required.
• Experience optimizing performance, scalability, reliability, and cost of enterprise data platforms is required.
• Demonstrated ability to solve highly complex technical and business problems in a collaborative environment is required.
• Ability to influence technical direction and engineering standards through expertise, mentorship, and technical leadership is required.

Nice To Haves

• Master's degree or equivalent advanced education is preferred.
• Equivalent combination of education and professional experience may be considered.
• Experience implementing DataOps, CI/CD, Infrastructure as Code, automated testing, and cloud engineering practices is preferred.
• Familiarity with data platforms that support Artificial Intelligence (AI), Machine Learning (ML), Generative AI, Agentic AI, and advanced analytics use cases is preferred.
• Property & Casualty insurance industry experience is strongly preferred.
• Strong understanding of insurance business domains including Policy, Claims, Underwriting, Billing, Agency, Customer, Finance, and Regulatory Reporting data is preferred.
• Experience integrating third-party data providers, vendor systems, APIs, and enterprise platforms is preferred.
• Databricks Certified Data Engineer Professional preferred.
• Microsoft Azure Data Engineer Associate (DP-203) preferred.
• Azure Solutions Architect Expert certification preferred.
• Certified Data Management Professional (CDMP) preferred.
• Familiarity with AI-assisted software development tools such as GitHub Copilot, Databricks Assistant, or equivalent AI coding and productivity tools is preferred.
• Ability to use AI-assisted engineering tools responsibly to improve development, testing, troubleshooting, and documentation is preferred.
• Azure Data Factory, Azure Storage, Azure Event Hub, Azure DevOps, Git, and Infrastructure as Code experience is preferred.

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 metadata management, lineage, data quality controls, stewardship processes, and security standards.
• Contribute to architecture reviews, code reviews, and technical design discussions across multiple projects and teams.
• Evaluate emerging technologies, tools, and architectural patterns to improve engineering productivity and platform capabilities.
• Mentor and provide technical guidance to data engineers through knowledge sharing and hands-on collaboration.
• Participate in troubleshooting, root-cause analysis, and resolution of complex data platform and production issues.
• Support AI, machine learning, and advanced analytics initiatives by enabling high-quality, accessible, and governed data foundations.
• Demonstrate behaviors consistent with PEMCO’s policies, values, code of ethics, and business conduct.
• Authentically support the PEMCO Brand and constantly be on the lookout for top talent to join us in achieving our Mission to Worry Less and Live More.
• Other duties as assigned.

Benefits

• Medical plans
• Dental plans
• Vision plans
• Employer premium cost shares
• Employer-paid basic life and accidental death & dismemberment insurance policies
• Long- and short-term disability benefit coverages
• 401(k) plan with a generous employer match (2 for 1 on the first 6% employee pre-tax and/or Roth deferral, up to federal maximums)
• Vacation
• Eight (8) paid holidays
• Four (4) floating holidays
• Up to ten (10) days of sick leave immediately upon hire (pro-rated based on hire date and full-time/part-time status)
• Paid time off for bereavement
• Paid time off for jury duty
• Paid time off for employee volunteering in the community
• Education Assistance Program after one year of service
• Scholarship program for children of PEMCO employees after one year of service
• Children’s birthday gift program
• Flexible Spending Accounts
• Employee Assistance Program
• Charitable gift matching
• Discretionary bonuses
• Tiered sales commissions and/or incentives

What This Job Offers

• Job Type: Full-time
• Career Level: Principal