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Engineering Manager – Data Experience

Engineering Manager – Data Experience

CompanyNetflix
LocationLos Gatos, CA, USA
Salary$100000 – $720000
TypeFull-Time
Degrees
Experience LevelSenior, Expert or higher

Requirements

  • 4+ years managing engineering teams, with a strong track record of growing individuals and delivering complex systems.
  • 8+ years of experience building modern web applications with deep expertise in full stack/frontend systems.
  • Proven experience developing internal tools or data-facing applications used by engineers, analysts, or ML practitioners.
  • Strong product instincts and the ability to align engineering efforts with user needs and platform value.
  • Ability to make sound, timely decisions in fast-paced environments with evolving priorities with a combination of data and intuition.
  • Demonstrated success in cross-functional collaboration across product, design, and adjacent engineering domains.

Responsibilities

  • Lead, mentor, and develop a team of UI engineers building a unified suite of data products across the data platform ecosystem.
  • Drive technical direction and architecture for frontend systems (React, TypeScript, GraphQL), balancing scalability, reusability, and simplicity.
  • Partner with Product, UX, and Backend Engineering to shape end-to-end data discovery north star experiences, enhancing data-driven decision-making through our data portal, query engine UI, and interactive tools.
  • Collaborate with infrastructure teams working on databases, stream processing platforms, storage systems, and query engines to align on APIs, capabilities, and integration patterns.
  • Make swift, high-quality decisions to unblock progress, reduce ambiguity, and uphold delivery momentum.
  • Champion best practices in accessibility, performance, and operational excellence for production-grade frontend systems.
  • Shape roadmap and priorities to maximize adoption, platform leverage, and end-user impact.

Preferred Qualifications

  • Experience building or contributing to data portals, query interfaces, notebook platforms, or stream processing UIs.
  • Familiarity with modern data infrastructure: Kafka, Flink, Trino, Iceberg, or internal developer platforms.
  • Experience with accessibility standards, testing frameworks, and design systems at scale.