Assistant Director of Data and Analytics Services

Assistant Director of Data & Analytics Engineering

Hybrid role (3 days/week in office) in our Portland, OR, Renton, WA, or Salt Lake City, UT offices. Candidates must reside within commutable distance of that location or be willing to relocate.

Build a career with purpose. Join our Cause to create a person-focused and economically sustainable health care system.

Every day, Cambia's dedicated team of data and analytics professionals is living our mission to make health care easier and lives better. As a member of the Data & Analytics Services (DAS) team, our Assistant Director of Data & Analytics Engineering leads data engineering teams responsible for building and sustaining enterprise data platforms — supporting analytics, purpose-built data products, and operational reporting across the enterprise — all in service of creating an economically sustainable health care system.

As a people leader, you are willing to learn and grow, understanding that leadership is a craft that is continuously honed as you support your team and the lives that depend upon us.

Do you bring a consulting-oriented mindset combined with deep hands-on data engineering expertise? Do you thrive leading high-performance teams through technological change while delivering measurable business value? Then this role may be the perfect fit.

What You Bring to Cambia:

• Bachelor's degree in Computer Science or related field (or equivalent experience)
• 5 years of combined demonstrated leadership experience in architecture, applications, or account management using current relevant technologies
• 7 years managing business or technology organizations with demonstrated competency in strategic thinking and leadership
• Experience managing SaaS products and teams may be required
• Excellent written and verbal communication skills with ability to interact with a wide range of stakeholders
• Thorough knowledge of finance, budget, and project management principles
• Demonstrated leadership of multi-disciplinary, high-performance teams across the full software development lifecycle
• Experience with architecture principles and design patterns across application types including web, integration, and business intelligence

• Deep expertise in data engineering, data warehousing, and analytics (OLAP), with solid familiarity in operational reporting and transactional processing (OLTP) requirements
• Hands‑on proficiency with modern cloud data platforms (Snowflake strongly preferred), dbt or equivalent ELT tools, SQL/Python stored procedures, and orchestration tools (Airflow/Open Flow or similar)
• Experience migrating platforms, integrating data, data profiling, performance optimization, and data governance/security/compliance
• Demonstrated success leading full system development lifecycle for data products and analytics solutions in complex enterprise environments, preferably healthcare/payer
• Experience with emerging capabilities such as semantic layers, metadata management, streaming data, Dev Ops/Data Ops, CI/CD for data, and AI/agentic analytics enablement
• Healthcare domain knowledge (Provider Network & Contract Management, Claims, Membership, Pricing, Alternate Payment Models, Shared Savings/Incentive Programs, Care Gap Management) highly desirable
• Demonstrated ability to leverage AI tools and resources to drive efficiency and innovation within area of expertise
• Strong servant leadership qualities with personal agility, innovation, flexibility, and perseverance in a rapidly changing environment
• Ability to manage through influence across formal and informal channels to gain alignment and synergy across stakeholders

• Lead and motivate teams of data engineers and managers to deliver on‑time, high‑quality, scalable data solutions — defining and communicating success in terms of value delivered to internal customers and business stakeholders
• Partner closely with data modeling, product, data governance, quality assurance, portfolio management, and business teams to design scalable data models and platform artifacts; optimize platform performance through query tuning, compute sizing, workload isolation, and…