Senior Data Engineer, Trust & Safety Data Enablement

Google

United States

On-site

USD 156,000 - 226,000

Full time

14 days+

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Job summary

Google in Austin, TX is seeking a Senior Data Engineer to design, build, and operate data platforms that support Trust and Safety and enable scalable reporting. You will work with policy teams to translate needs into robust data architectures that drive safety and compliance decisions.

You will craft unified data pipelines, profile large datasets for insights, and guide best practices for data lifecycle management. Collaboration across engineering and policy is essential in this role.

Qualifications

  • Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
  • 5 years of experience with SQL or Python.
  • Experience working with data modeling, data storage, or data management.

Responsibilities

  • Design, build, and maintain data processing systems and data structures that handle legal content removal and compliance reporting.
  • Collaborate with policy specialists and cross-functional partners to understand business needs and translate them into robust technical data designs.
  • Create unified data pipelines and models to simplify data access, reduce duplication, and establish clear sources of truth.
  • Analyze and profile large datasets to uncover trends, improve data quality, and enable data-driven operational decisions.
  • Guide engineering best practices for data life-cycle management, storage design, and data discoverability.

Skills

SQL
Python
Data modeling

Education

Bachelor's degree or equivalent practical experience

Job description

Google in Austin, TX is seeking a Senior Data Engineer to design, build, and operate data platforms that support Trust and Safety and enable scalable reporting. You will work with policy teams to translate needs into robust data architectures that drive safety and compliance decisions.

You will craft unified data pipelines, profile large datasets for insights, and guide best practices for data lifecycle management. Collaboration across engineering and policy is essential in this role.

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