Data Engineering Manager

Google LLC
  • Mountain View, CA
    3 days ago

    Job Description

    Data Engineering Manager

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    corporate_fareGoogleplaceMountain View, CA, USA

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    Advanced

    Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

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

    Minimum qualifications:

    • Bachelors 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.

    Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Googles Applicant and Candidate Privacy Policy.

    Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Googles EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

    If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

    Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

    To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

    Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

    Numbers & Facts

    LocationMountain View, CA

    Skills

    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Cloud Computingunmatched
    • Code Reviewsunmatched
    • Communication Skillsunmatched
    • Consumer Electronicsunmatched
    • Data Analysisunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Qualityunmatched
    • Data Scienceunmatched
    • Data Setsunmatched
    • Data Warehousingunmatched
    • Database Extract Transform and Load (ETL)unmatched
    • Engineering Managementunmatched
    • English Languageunmatched
    • Equal Employment Opportunity (EEO)unmatched
    • Establish Prioritiesunmatched
    • GCP (Good Clinical Practices)unmatched
    • Geneticsunmatched
    • Operational Strategyunmatched
    • People Managementunmatched
    • Product Strategyunmatched
    • Programming Languagesunmatched
    • Recruiting/Staffing Agencyunmatched
    • Regulatory Requirementsunmatched
    • Resource Managementunmatched
    • SQL (Structured Query Language)unmatched
    • Scalable System Developmentunmatched
    • Scripting (Scripting Languages)unmatched
    • Stock Purchase Plansunmatched
    • Supply Chainunmatched
    • Team Lead/Managerunmatched
    • Technical Leadershipunmatched
    • Technical Strategyunmatched
    • Technical/Engineering Designunmatched
    • Time Managementunmatched

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