Data Engineer, Google Trust and Safety

1 Month ago • 3-6 Years • Data Analyst • $124,000 PA - $178,000 PA

Job Summary

Job Description

The Data Engineer will design and develop data infrastructure supporting metrics and measurement for Trust and Safety across Google products (Search, Ads, Play, etc.). Responsibilities include designing and implementing analytics and reporting solutions, collaborating with stakeholders, productionizing analytics and models, and managing data pipelines. The role requires proficiency in SQL, Python, data modeling, and experience with big data technologies (e.g., DataFlow, Spark). The engineer will ensure stakeholders have the data needed for crucial business decisions and regulatory reporting.
Must have:
  • 3+ years data infrastructure & modeling experience
  • 3+ years designing data pipelines
  • 3+ years SQL & Python (or Java/C++) experience
  • Design & develop data infrastructure for reporting
  • Implement & optimize analytics & reporting solutions
Good to have:
  • 3+ years statistical methodology experience
  • Experience with business intelligence tools
  • Experience with Machine Learning for production workflows
  • Stakeholder management & project delivery experience
Perks:
  • bonus
  • equity
  • benefits

Job Details

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 3 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
  • 3 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.).
  • 3 years of experience with SQL and Python (or Java/C++).

Preferred qualifications:

  • 3 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.
  • 3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
  • 3 years of experience developing project plans and delivering projects on time within budget and scope.
  • Experience with Machine Learning for production workflows.

About the job

gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Google's Ads products into customer experiences that are so intuitive (or automated) that they require no support at all. gPTO partners closely with gTech’s Support, Professional Services, Product Management, and Engineering teams to innovate and simplify our Ads products and build the productivity tools ecosystem for gTech users.

As part of this team, you will be responsible for designing and developing the data infrastructure needed to support metrics and measurement capabilities for Trust and Safety across various Google products, including Search, Ads, Play, Shopping, Publishers, and YouTube business generation. You will ensure stakeholders have the product, support, and operations data they need to make crucial business decisions. You will have the opportunity to design innovative data solutions and solve challenging problems using Google’s production data infrastructure to drive business optimization and meet regulatory reporting requirements.

The US base salary range for this full-time position is $124,000-$178,000 + 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 .

Responsibilities

  • Acquire understanding of business processes, tools and customer expectations and design and develop data infrastructure to support reporting needs.
  • Design, implement, test, optimize and troubleshoot analytics and reporting solutions to solve business performance management challenges as well as to meet regulatory reporting requirements.
  • Collaborate with and influence business and engineering stakeholders to ensure our data infrastructure and products meets constantly evolving requirements.
  • Work closely with analysts to productionize analytics and reporting prototypes, and various statistical and machine learning models.
  • Design, implement and own technical implementation of production-level data pipelines, documentation, check-in process, etc.

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