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Software Engineering Manager, Ads Analytics, Insights and Measurements, Full Stack

Google3,348 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowSoftware Engineering Manager, Ads Analytics, Insights and Measurements, Full StackGoogle · Mountain View, CA, USA
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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. 1.6%1 day
  2. 3.4%3 days
  3. 7.8%7 days
  4. 14.3%14 days
  5. 33.6%30 days
This job: first seen 14 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.
  • 8 years of experience in software development.
  • 3 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
  • 3 years of experience in a technical leadership role.
  • 2 years of experience in a people management or team leadership role.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 3 years of experience working in a complex, matrixed organization.

About the job

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

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

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  • Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
  • Develop the mid-term technical goals and roadmap within the scope of your (often multiple) team(s). Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  • Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
  • Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
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