Data Engineer, Trust and Safety Consumer Analytics

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 4 years of experience in data analytics, Trust & Safety, policy, cybersecurity, or related fields.
• 3 years of experience working with business analytics or data analysis.
• Experience with code optimization and in SQL, Python, or R.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 3 years of experience in large-scale distributed data processing.
• Experience designing data warehouses, especially for business performance management including: data processing automation, data quality, data warehousing, data governance, business intelligence, data visualization, data privacy.
• Experience with machine learning and familiarity with NoSQL databases.
• Excellent communication and presentation skills (written and verbal) and the ability to influence cross-functionally at various levels.

About the job

At Google we work hard to earn our users' trust every day. Gaining and retaining this trust is critically important to Google's success. The Trust and Safety team reduces risk and protects the experience of our users and business partners in more than 40 languages and across Google's expanding base of products. We defend Google's integrity by fighting spam, fraud and abuse, and develop and communicate state-of-the-art product policies. We work with a variety of teams from Engineering to Legal, Public Policy, and Sales Engineering to set policies and combat fraud and abuse in a scalable way, often with an eye to finding industry-wide solutions. Trust and Safety team members are motivated to find innovative solutions, and use technical know-how, user insights, and proactive communication to pursue the highest possible quality and safety standards for users across Google products.

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, Shopping, Publishers, and YouTube. You'll ensure stakeholders have the product, support, and operations data they need to make crucial business decisions. You'll have the opportunity to design innovative data solutions and solve challenging problems using Google's large-scale production data infrastructure to drive business optimization and meet regulatory reporting requirements.

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 diverse 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 $108,000-$158,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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

• Design, implement, test, optimize, and troubleshoot analytics and reporting solutions to solve business performance management challenges as well as 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. Write and review technical documents including design, requirements, and process documentation.
• Acquire deep understanding of business processes, tools and customer expectations, and design and develop scalable data infrastructure to support reporting needs.