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Sr. Manager AI, Data and QA

Remote / Online - Candidates ideally in
Portland, Multnomah County, Oregon, 97204, USA
Listing for: NW Natural
Full Time, Remote/Work from Home position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    IT Project Manager, Data Analyst
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Sr. Manager AI, Data and QA

Non‑Union Position
Enterprise Applications;
Portland, Oregon (US‑OR)

Hybrid schedule available for Oregon & Washington residents. Regular FT, Exempt. Posting # 5484

About Us

At NW Natural, we offer more than rewarding career opportunities and a vibrant, inclusive work culture. We invite you to join us in providing safe and reliable utility services and renewable energy to better the lives of the communities we serve. Our vision is to be the leader in service excellence, innovation and environmental stewardship for our customers while building on our strengths as a trusted energy provider and environmental leader for our industry.

In addition to environmental stewardship, we’re also deeply committed to Diversity, Equity and Inclusion at NW Natural. Our DEI Council started 21 years ago, and today we continue to foster a culture where all employees can experience a sense of belonging, shared purpose and possibility.

NOTE

Employees based at our Headquarters are required to work on‑site a minimum of two days per week. Specific in‑office days may vary by team and business needs. This hybrid schedule supports collaboration, connection, and engagement while also offering flexibility for remote work.

The Role

The Senior Manager of AI, Data & QA is responsible for driving enterprise data strategy, advancing AI and automation capabilities, and elevating quality assurance practices across the company. This leader oversees data professionals, AI/ML practitioners, and QA experts to deliver trusted data products, insights, AI‑enabled solutions, and high‑quality technology outcomes.

Day to Day AI & Machine Learning Leadership
  • Work collaboratively with the Enterprise Architecture team to formulate and execute an organization‑wide AI strategy aligned with business goals. This includes leading the development of governance frameworks.
  • Work with business stakeholders to identify opportunities where AI and automation can add value, driving the successful delivery of these initiatives to improve efficiency throughout the company.
  • Lead change management efforts to promote enterprise‑wide adoption of AI by developing training programs, creating playbooks, and managing the Center of Excellence for best practices and continuous learning.
Data & Analytics Leadership
  • Lead the full lifecycle of data projects, overseeing the ongoing enhancement of the enterprise data platform and the growth of self‑service and advanced analytics capabilities.
  • Collaborate with Enterprise Architecture to advance the data platform technology roadmap and support data governance by developing and applying standards and programs that improve data quality across the organization.
  • Direct data engineering and analytics teams to deliver scalable and secure solutions that effectively address business requirements.
Quality Assurance Leadership
  • Develop and implement a comprehensive enterprise Quality Assurance (QA) strategy, establishing standards and governance processes to ensure consistency and excellence.
  • Lead and coordinate testing efforts for IT projects and operational initiatives, maintaining robust QA practices across the organization.
  • Champion the adoption of QA automation, monitor key performance metrics, and drive ongoing improvements to enhance overall quality and efficiency.
Team & Stakeholder Leadership
  • Lead, develop, and mentor multidisciplinary teams specializing in data, artificial intelligence, and quality assurance to drive organizational success.
  • Collaborate with senior leadership, the Project Management Office (PMO), enterprise architects, and key business stakeholders to align strategic objectives.
  • Direct resource allocation and oversee portfolio prioritization to ensure optimal delivery of initiatives and maximize business impact.
Come on your first day with:
  • 10+ years across data, analytics, AI/ML, and QA; 5+ years leading technical teams.
  • Experience with modern data stacks (e.g., Azure, Databricks, Snowflake, Power BI).
  • Demonstrated QA methodology and SDLC expertise.
  • Excellent communication and leadership skills.
What we offer Health & Wellness
  • Rich health insurance benefits with competitive employer contribution.
  • Free access…
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