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Google
Google

Organizing the world's information and making it universally accessible.

Software Engineer, Personalization Platform, Core

RoleEngineering
LevelMid Level
WorkOn-site
TypeFull-time
Posted1 month ago
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About the job

The Personalization Data team is a horizontal initiative in Core User Data to provide Google-wide shared infrastructure for managing personalization User Data storage and User Profile building as a service.The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

  • Develop code for products or systems. Participate in design reviews with peers and stakeholders to evaluate technology options.

  • Review and provide feedback on code developed by other developers to ensure adherence to best practices including, accuracy,  and efficiency.

  • Maintain existing documentation or educational content, revising it based on product/program updates and user feedback.

  • Contribute to full life cycle of personalization profiling infrastructure at Google-scale. Process infrastructure to create user profiles offline or online with built in compliance, using machine learning inference on a user’s activity timeline or SQL-based aggregation of user activities.

Minimum qualifications

  • Bachelor’s degree or equivalent practical experience.

  • 2 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture

  • 2 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.

  • Experience with C++.

Preferred qualifications

  • Master's degree or PhD in Computer Science or related technical field.

  • Experience operating in production and ability to work closely with User Data Site Reliability Engineering.

  • Experience with and interest in Google-scale infrastructure since we work closely with partner teams.

  • Passion for solving customer problems.

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About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

10 reviews

4.5

10 reviews

Work-life balance

3.2

Compensation

4.3

Culture

4.1

Career

4.2

Management

3.8

82%

Recommend to a friend

Pros

Great benefits and perks

Innovative and interesting work

Career development and learning opportunities

Cons

High pressure and expectations

Long hours and heavy workload

Fast-paced and overwhelming environment

Salary Ranges

57,503 data points

Mid/L4

Mid/L4 · Accessibility Analyst

1 reports

$214,500

total per year

Base

$165,000

Stock

-

Bonus

-

$214,500

$214,500

Interview experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense