Data Engineer, Platforms and Devices

Google; Mountain View (CA); On-site; USD 150,000 - 220,000; Full time

Job summary

Join Google as a Data Engineer in the Platforms and Devices team to build and maintain data processing and machine learning software. Your role will involve optimizing data infrastructure and collaborating with analysts to enhance decision-making in product development. This position offers a competitive salary and the opportunity to work on innovative products, impacting millions of users worldwide.

Benefits

Bonus

Equity

Comprehensive benefits

Qualifications

• 5 years of experience designing data pipelines.
• 5 years of experience coding in one or more programming languages.
• Understanding of machine learning.

Responsibilities

• Build and maintain data processing pipelines.
• Gather requirements from analysts and data scientists.
• Write and review technical documentation.

Skills

Data pipelines design

Dimensional data modeling

Software development

Data infrastructure

SQL

Machine learning

Education

Bachelor's degree or equivalent

Tools

BigQuery

Spark

NoSQL

Dataflow

Cloud Build

Job description

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Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Chicago, IL, USA.Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).
• 5 years of experience coding in one or more programming languages.
• 5 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
  
  

Preferred qualifications:

• Experience using SQL in a large-scale investigative, NoSQL, columnar context.
• Experience using continuous integration and deployment systems (e.g., Cloud Build, GitLab, Jenkins).
• Experience writing unit tests (e.g., PyTest, Selenium, JUnit).
• Understanding of machine learning.
  
  

About the jobThe Platforms and Devices (P&D) product area is responsible for many popular consumer-facing products including the Android and ChromeOS operating systems as well as many hardware and subscription products, like Pixel phones, smart home devices, and Google One. Within Platforms and Devices, the Insights and Analytics group’s mission is to use data to help the product area make better decisions. The Data Engineering team supports that work by building and maintaining data processing, machine learning, and automation software to solve, scale and efficiency problems.

In this role, you will have a background in distributed data processing, investigative thinking, machine learning, and software development.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

The US base salary range for this full-time position is $150,000-$220,000 + 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

• Gather requirements from analysts, data scientists, and business stakeholders and understand how they fit into larger business priorities.
• Build, optimize and maintain data infrastructure including large-scale data processing pipelines (e.g., ETL; BigQuery, Snowflake, Redshift or Dataflow, Beam, Spark jobs), ML model training/tuning (e.g., AutoML) and inference pipelines and orchestration workflows (e.g., Cloud Composer, Airflow, Prefect).
• Advocate engineering best practices within the team and outside of it by writing and reviewing technical documentation, writing highly-readable and style-conformant code, and leading training.
• Stay up to date and comply with complicated and ever-changing policy and governance requirements.
  
  
  

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Project Management, Consulting, and Engineering

• Industries

  Information Services and Technology, Information and Internet

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