Sr. Technical Program Manager, Platform & Data (Hybrid - Seattle, WA)

Nordstrom•Seattle, WA

1d•Hybrid

About The Position

Join Nordstrom’s Platform and Data (PND) organization as a Senior Technical Program Manager (TPM) on the Insights Delivery team. In this pivotal role, you will drive AI-first metric definition/standardization and data quality programs that empower engineers, product managers, and business leaders to make trusted decisions at scale. You will partner with data engineering and analytics teams to shape how Nordstrom defines, governs, and delivers metrics—using AI as a force multiplier throughout. You will partner with cross-functional teams to ensure data governance practices are embedded into our data platforms, analytics solutions, and business processes—enabling trusted, high-quality data for decision-making. The ideal candidate brings deep experience in technical program management, data engineering and/or analytics, and enterprise data strategy. You will lead the scaling and maturation of Nordstrom’s enterprise data governance operating model—expanding adoption and impact through AI-first ways of working. In close partnership with business leaders, engineering, and product, you will continuously refine and evolve the operating model to meet changing organizational needs, while ensuring governance capabilities are practical, measurable, and adopted at enterprise scale. A day in the life… Scale and mature Nordstrom’s enterprise data governance operating model—strengthening ownership, stewardship, data quality, and AI-first metric standardization so leaders can rely on consistent, trusted reporting. Drive execution by owning roadmaps, timelines, dependencies, and delivery across governance initiatives, surfacing risks and trade-offs early. Partner with product, engineering, data platform, analytics, and business leaders (e.g., Supply Chain, Customer, Marketing, Merchandising) to embed governance into end-to-end data lifecycle workflows and tools—and align priorities, requirements, and adoption. Lead change and alignment through workshops, clear communications, and enablement—building shared understanding, adoption, and accountability for high-quality, well-governed data. You own this if you have... Bachelor’s degree in Computer Science, Information Systems, Business, or a related field (Master’s preferred), or equivalent practical experience. 7+ years of experience in technical program management, with a focus on data engineering, analytics, or a closely related data discipline. Proven experience delivering complex, cross-functional programs in a matrixed organization—partnering across product, engineering, data platform, analytics, and business to operationalize enterprise metrics and measurement frameworks and drive outcomes ready for leadership reporting. Demonstrated ability to influence senior product and engineering leaders through clear communication, sound judgment, and data-grounded problem solving—driving alignment and decisions in ambiguous environments. Exceptional storytelling and executive communication skills: able to translate data, engineering progress, and program status into narratives that resonate with executives, domain leaders, and non-technical audiences. Experience supporting executive-level operating rhythms (e.g., weekly business reviews, steering committees, etc.), translating strategy into measurable outcomes and durable execution plans. Strong technical foundation with the ability to partner effectively on data pipelines and AI-enabled tools—helping teams diagnose issues, weigh trade-offs, and drive resolution. Working knowledge of SQL, with the ability to read and review queries to understand data logic, validate results, and troubleshoot issues; experience with Python, R, or similar tools for analysis, automation, experimentation support, and/or data validation is a plus. Understanding of modern data platforms (e.g. Google Cloud Platform, Databricks, Azure) and familiarity with data cataloging tools (e.g. DataHub, Collibra) is a plus.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Business, or a related field (Master’s preferred), or equivalent practical experience.
7+ years of experience in technical program management, with a focus on data engineering, analytics, or a closely related data discipline.
Proven experience delivering complex, cross-functional programs in a matrixed organization—partnering across product, engineering, data platform, analytics, and business to operationalize enterprise metrics and measurement frameworks and drive outcomes ready for leadership reporting.
Demonstrated ability to influence senior product and engineering leaders through clear communication, sound judgment, and data-grounded problem solving—driving alignment and decisions in ambiguous environments.
Exceptional storytelling and executive communication skills: able to translate data, engineering progress, and program status into narratives that resonate with executives, domain leaders, and non-technical audiences.
Experience supporting executive-level operating rhythms (e.g., weekly business reviews, steering committees, etc.), translating strategy into measurable outcomes and durable execution plans.
Strong technical foundation with the ability to partner effectively on data pipelines and AI-enabled tools—helping teams diagnose issues, weigh trade-offs, and drive resolution.
Working knowledge of SQL, with the ability to read and review queries to understand data logic, validate results, and troubleshoot issues; experience with Python, R, or similar tools for analysis, automation, experimentation support, and/or data validation is a plus.
Understanding of modern data platforms (e.g. Google Cloud Platform, Databricks, Azure) and familiarity with data cataloging tools (e.g. DataHub, Collibra) is a plus.

Nice To Haves

PMP, Agile, or Scrum certification(s) are a plus.

Responsibilities

Scale and mature Nordstrom’s enterprise data governance operating model—strengthening ownership, stewardship, data quality, and AI-first metric standardization so leaders can rely on consistent, trusted reporting.
Drive execution by owning roadmaps, timelines, dependencies, and delivery across governance initiatives, surfacing risks and trade-offs early.
Partner with product, engineering, data platform, analytics, and business leaders (e.g., Supply Chain, Customer, Marketing, Merchandising) to embed governance into end-to-end data lifecycle workflows and tools—and align priorities, requirements, and adoption.
Lead change and alignment through workshops, clear communications, and enablement—building shared understanding, adoption, and accountability for high-quality, well-governed data.