Senior Data Engineer, gTech Risk

Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products. In this role, you will protect Google and its users by identifying and implementing controls for significant risks. To ensure gTech's security and agility, the team analyzes gTech business processes to find control gaps, collaborates with stakeholders to resolve these gaps, and provides risk expertise to engineer solutions. Within this organization, the Risk Strategy and Engagement pillar serves as the intelligence core and the primary bridge to our business partnersGoogle creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products. To learn more about gTech, check out our video .Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . Develop and maintain the data architecture and predictive models powering gTech’s risk graph. Design and deploy automated key risk indicators (rKRIs) across all gTech workflows, replacing manual, point in time reporting. Integrate gTech operational data with central enterprise risk platforms to create a single, automated source of truth. Partner with core Data Science and Engineering teams to transition our risk analysis from reactive (incident based) to predictive (threat based). Build and manage executive dashboards for business reviews, pipeline management, and enterprise risk posture reporting. Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 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.). Experience with Python or R for statistical analysis and model development. Experience in SQL and data visualization tools (e.g., Tableau, Looker). Preferred qualifications: Master's degree in Data Science, Statistics, Computer Science, Economics, or equivalent practical experience. 6 years of experience in data analytics, data modeling, or risk quantification. Experience working within an Enterprise Risk Management (ERM) or Governance, Risk, and Compliance (GRC) framework. Bachelor's degree or equivalent practical experience. 5 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.). Experience with Python or R for statistical analysis and model development. Experience in SQL and data visualization tools (e.g., Tableau, Looker).