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Open nowFirst seen 2 hours ago

Data Engineering Manager

Google3,566 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowData Engineering ManagerGoogle · Mountain View, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

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The clock on this job

Early applications get read.

9.5% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 28 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.9%3 days
  3. 9.5%7 days
  4. 15.5%14 days
  5. 33.9%30 days
This job: first seen 2 hours ago

Google median: 28 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
  • 5 years of experience coding in one or more programming languages, designing data pipelines, and experience with data warehousing concepts, data modeling techniques, and scalable architecture patterns.
  • 3 years of experience in a people management, supervision, or team leadership role.

Preferred qualifications:

  • Experience with GCP data services (BigQuery) or other cloud platforms data services, AI infrastructure (Vertex AI), and making build-versus-buy decisions.
  • Experience driving AI data strategy, including Generative AI, LLM integration, RAG, and vector databases.
  • Experience setting up data quality, governance, reliability frameworks, and production-grade pipeline engineering standards.
  • Experience setting technical roadmaps, managing priorities, and delivering projects across teams.
  • Experience or familiarity with consumer electronics, or supply chain data.
  • Executive communication skills to influence leaders, and building high-performing teams.

About the job

The Data and Analytics Services (DAS) team is a data and analytics hub for the Google Platforms and Devices (P&D) organization. Our mission is to empower the Devices organization with timely, accurate, and actionable data. We build scalable analytics solutions on Google Cloud Platform. By partnering closely with business stakeholders, we translate complex data needs into tangible technical solutions that drive decision-making, product strategy, and operational efficiency via data-driven insights and advanced AI applications. We are committed to ensuring that data is a reliable and transformative asset for all of P&D.

As the Manager, Data Engineering on the DAS team, you will lead a team of data engineers designing and building the next generation of our data infrastructure.

This role needs a strong technical leader who can manage and inspire high-performing data engineers while staying close enough to the work to guide architecture decisions on massive datasets. You will be a partner to functional teams, turning business needs into prioritized solutions. You will also set the standards and best practices that raise the bar across the organization.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $186000 - $269000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Define the technical strategy for the centralized data warehouse, including scalable pipelines, ETL/ELT processes, and AI-ready data foundations.
  • Oversee performant data modeling and SQL transformation standards, guiding architecture and optimization to support analytics at scale.
  • Drive organization-wide data quality, governance, and operational reliability, holding the team accountable for trusted data assets.
  • Partner with executive leaders, data scientists, and engineering teams to translate complex business needs into prioritized roadmaps.
  • Manage resources and capacity to deliver projects on time while promoting best practices like code and design reviews.
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