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Open nowFirst seen 6 hours ago

Senior Software Engineer, Analytics Engineering

Google3,370 open roles

Where
San Jose, CA, USA
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Your applicationOpen nowSenior Software Engineer, Analytics EngineeringGoogle · San Jose, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: first seen 6 hours ago

Google median: 26 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.
  • 5 years of experience with software development in one or more programming languages.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • Experience programming in Java and Python.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • Experience building web frontends and rich data visualization interfaces.
  • Experience in data pipelines, analysis, visualization, and insights generation.
  • Technical leadership capabilities, including the ability to enhance existing workflows and processes, design solutions, and implement effectively.
  • Excellent programming proficiency in Java, Flume, and Python.

About the job

Our AI Systems Knowledge and Intelligence Engine (ASKIE) team is seeking a full stack insights Senior Software Engineer. In this role, you will be responsible for building Google's premier AI observability web applications. You will sit at the intersection of product, design, and data infrastructure—partnering closely with Product Managers, UX Designers, UX Researchers, and Data Scientists to build intuitive, high-performance executive dashboards and self-service analytics tools for senior leaders (e.g., VPs, SVPs, and Directors) and engineering teams across all of Alphabet.

The Analytics Engineering team within ASKIE build the production-grade data pipelines, telemetry foundations, and visualization platforms that measure the transformation, velocity, and economic impact of AI across Google. We architect the foundational intelligence layer for Google's agentic ecosystem, engineering the data, insights, and feedback loops that empower developers and autonomous agents. We serve as the headlights for the organization and the company—lighting the road for self-driving software engineering capabilities.

As part of the ASKIE engineering culture, you will be at the edge of AI-native software engineering—actively embracing AI agents and autonomous workflows in your daily product development lifecycle (PDLC) while pioneering the use of Google’s productionized and experimental AI product portfolio.

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

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Architect and implement high-performance, responsive web interfaces and backend serving layers for Agentrics and related AI observability suites.
  • Advocate for the adoption of AI-first development practices in everyday engineering workflows, leveraging agentic coding assistants, autonomous test harnesses, and automated review agents.
  • Develop self-service capabilities allowing leaders and team leads to customize views, configure ad-hoc metric explorations, and inspect organization-wide AI adoption metrics.
  • Implement custom data visualization components using modern charting libraries.
  • Design, build, and optimize low-latency backend APIs to deliver sub-second response times across large datasets.
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