Engineering Analyst, Trust and Safety, Intel Collections

Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.

The Engineering Analyst will drive crucial AI and automation efforts to scale internal tooling, specifically by building the infrastructure that powers our threat discovery through external data integration and automated detection systems. You will architect and implement technical solutions using scripting languages, database design, and system architecture to optimize daily workflows. You'll serve as a critical technical bridge across intel and core engineering teams to ensure operational needs align seamlessly with broader strategic goals. In addition, you will translate complex system capabilities into actionable strategies, advocating for AI adoption and educating cross-functional stakeholders to drive long-term organizational efficiency.

At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.

The US base salary range for this full-time position is $132,000-$189,000 + 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

• Build and maintain automated data pipelines, reporting dashboards, and reusable frameworks. This competency includes the skill to gather requirements from non-technical stakeholders and transform raw data into clear, actionable visualizations and reports.
• Act as a crucial link between intelligence analysts and product, engineering, and policy teams. This includes communicating effectively with intel analysts and collaborating to ensure their outputs are integrated into product features and enforcement systems, and creating feedback loops that inform system improvements.
• Develop and refine prompt sets for large language models to leverage AI models through automation to maximize workflows. Conduct quality checks and data validation to ensure the accuracy and integrity of all data and prompts used in production systems. 
• This role works with sensitive content or situations and may be exposed to graphic, controversial, and/or upsetting topics or content.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
  
• 2 years of experience managing projects and defining project scope, goals, and deliverables.
  

Preferred qualifications:

• Master's degree in a quantitative discipline.
  
• 2 years of experience or familiarity with one or more of the following languages: SQL, R, Python, or C++.
• 2 years of experience or familiarity with machine learning systems.
  
• Excellent written and verbal communication skills.
  
• Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.