Data Engineering Lead, Google Trust and Safety

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
• 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks.
• 3 years of experience in a people management, supervision, or team leadership role.

Preferred qualifications:

• 5 years of experience partnering with stakeholders (e.g., users, partners, customers), and managing stakeholders/customers.
• 5 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.
• 5 years of experience developing project plans and delivering projects on time.
• 3 years of 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 business decisions. You will have the opportunity to design data solutions and solve problems using Google’s large-scale production data infrastructure to drive business optimization and meet regulatory reporting requirements.

Responsibilities

• Lead a team of individuals, set and communicate individual and team priorities that support organizational goals. Meet regularly with individuals to discuss performance and development, and provide feedback and coaching.
• Understand the business processes, tools and customer expectations and design. 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.
• Write and review technical documents, including design, requirements, and process documentation.