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Technical Product Lead, Deal and Payment Solutions, YouTube
2 weeks ago
- Bachelor's degree or equivalent practical experience.
- 3 years of experience troubleshooting technical issues for internal/external partners or customers.
- 3 years of experience with data analysis and SQL/MySQL.
- Experience in system architecture and code comprehension/reading in one programming language (e.g., Java, C++, Python).
- Master's degree in Business, Statistics, Mathematics, Economics, Engineering or Applied Science, or a related field.
- 5 years of experience managing projects and working with analytics, software coding, or customer-side web technologies.
- 5 years of experience in a customer-facing role.
- 5 years of experience in operations management (i.e. process improvement, operational reviews, optimizing workflows, etc).
- Experience drawing insights from large data sets using SQL to drive both business and technology decisions.
As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships.
You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.
In this role, you will play the central role in defining and implementing the strategy for how we validate, measure, and govern the critical data that powers YouTube's negotiations and partner payments.You will develop strategies for validating data at scale, establish the metrics and build the dashboards that measure data accuracy, design rules-based engines to check data quality, and own the operational workflows for our human-in-the-loop review teams.
You will own the product goal for our contract creation platform built on Salesforce, working with engineering to simplify complex workflows, achieving unprecedented scale and accuracy. You will own the data quality life-cycle, from strategic ideation to operational execution, and see your work directly influence YouTube's bottom line.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.
Responsibilities:- Lead the strategy and design of products and capabilities that ensure the integrity of data across YouTube's business organization.Own the data quality life-cycle the goal, roadmap, prioritization, research, requirements, and execution for all data validation initiatives.
- Partner with engineering teams to translate your data quality strategies into technical solutions, including rules-based engines and data model enhancements.
Partner on the product strategy for AI-driven products like our automated contract term extraction tool. - Write and execute complex SQL queries to perform in-depth search data analysis, identifying patterns and opportunities for quality improvement.
- Design, build, and maintain a suite of dashboards and reports that provide a real-time view of data accuracy and completeness for stakeholders.
- Communicate insights and build consensus across cross-functional teams, the importance of data quality.
