Engineering Manager: Engineering Data Platform Enablement (Hybrid, Seattle - WA)

Nordstrom•Seattle, WA

1d•Hybrid

About The Position

Data Platform Enablement keeps Nordstrom's analytics and data platforms running, evolving, and getting simpler. We own a broad portfolio across GCP and AWS — BigQuery, Looker Core, Metabase, and the access management and cost optimization that keep them healthy. We're a small team covering a large surface area, and AI is how we do it. This is a player-coach role. You own delivery, technical standards, operational health, and the growth of your engineers — and you stay hands-on, writing code and building automation alongside them. You partner with a Product Manager who owns vision and stakeholders, while you own technical delivery, architecture, and team health. We use AI every day — not occasionally — to write code, automate operations, and investigate incidents. We run Kanban with continuous flow and weekly demos: no sprints, no story points. Our engineers are generalists who work across the whole portfolio, pair, cross-train, and value direct contribution over process.

Requirements

2+ years leading engineering teams, with direct accountability for delivery and people development
5+ years building software, platforms, infrastructure, or data systems
Hands-on Python proficiency (or equivalent) you still write today — direct technical contribution is expected
Strong cloud experience across GCP and/or AWS, with fluency in Git, CI/CD, and infrastructure as code
Experience owning access management programs at scale
Daily use of AI coding tools and a real point of view on how they change the way teams work

Nice To Haves

Data platform or BI depth: BigQuery, Looker, Metabase, Tableau, or MicroStrategy
Terraform and Kubernetes
Cloud cost optimization at scale
Analytics access provisioning in SailPoint IdentityNow via SCIM group synchronization
Hands-on Dataplex zone governance
Experience standing up an AI-first engineering practice
Familiarity with Conversational Analytics, LLM-powered data tools, or semantic layer patterns
Experience at a large-scale retail, e-commerce, or consumer organization

Responsibilities

Lead engineering delivery across BigQuery/GCP, GCP Looker, Metabase, and AWS workloads
Own platform reliability, incident response, and on-call for production systems
Drive capacity planning — forecasting growth, managing compute costs, and scaling ahead of demand
Support the deprecation of legacy platforms (MicroStrategy, Tableau)
Own enterprise access provisioning and governance across the data platform
Lead cost optimization across GCP, AWS, and platform tooling in partnership with engineering and finance
Define access policies, tiering models, and provisioning workflows with security and compliance partners
Establish LookML governance, development standards, and deployment practices for Looker Core
Partner with analytics teams on explore design, data modeling, and dashboard best practices
Own platform health, migration governance, and the Looker development lifecycle
Lead the CA enablement strategy — Golden Query standards, agent development, adoption
Manage token utilization and capacity planning with Insights Delivery leadership
Partner with every team across the organization to drive CA maturity enterprise-wide
Set technical direction: architecture, standards, monitoring, and prioritization
Develop your engineers and coach AI fluency through hands-on guidance and a high adoption bar
Contribute as an engineer: write code, build tooling, and review pull requests alongside the team
Own hiring, capacity planning, and team health