Build reusable data-to-AI solutions, architectures, and accelerators with partners on Google Cloud
Design and implement governed semantic layers and enterprise ontologies connecting BigQuery Graph, Conversational Analytics Agents, Looker, and Google Cloud Knowledge Catalog Custom Aspects to ground enterprise AI agents in verified business definitions
Validate Gemini Enterprise plugins, remote Model Context Protocol (MCP) servers, and reusable agent skills that integrate Google Data Cloud services with third-party enterprise systems
Develop internal AI-assisted validation tools, evaluation rubrics, and automated architectural review workflows that scale Partner Engineering quality and turnaround velocity across partner engagements
Lead technical onboarding for Data and AI launches, developing implementation guides, code assets, and enablement materials
Requirements
Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field
Lead product strategy and execution for Google’s attribution modeling portfolio, driving cross-functional collaboration and AI-driven measurement solutions.
Define the multi-year direction and roadmap for Google’s core attribution modeling portfolio across Google Ads, Google Analytics, and Google Marketing Platform (GMP)
Manage the full product lifecycle—from opportunity sizing in SQL/Plx and authoring product required documents to navigating complex cross-product area launch approvals, running causal impact experiments, and validating realized business growth with Finance
As an Engineering Analyst in the Trust and Safety Search, you will work to discover, measure and mitigate user trust risks in Search through automated and scalable solutions.
Develop domain knowledge in Search infrastructure, ranking signals, and products.
Develop prompt-based AI Raters that can evaluate content safety in Google products.
Investigate and analyze complex patterns of badness and abuse on Google Search, utilizing data-driven insights to develop countermeasures and enhance platform security.
Analyze large datasets to identify trends, patterns, and anomalies that may indicate abuse or quality issues within Google Search.
Collaborate effectively with cross-functional teams, including Engineering, Product, Policy, and Legal, to develop and implement robust solutions that enhance search quality and user trust.
Financial Analysts ensure that Google makes sound financial decisions by modeling business scenarios, tracking performance metrics, and providing strategic analysis.
Perform analysis of datasets to extract relevant information, identify trends, and generate actionable insights for the business.
Identify, evaluate, and prioritize risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events or to maximize the realization of opportunities.
Financial Analysts ensure that Google makes sound financial decisions. As a Financial Analyst, your work, whether it's modeling business scenarios or tracking performance metrics, is used by our leaders to make strategic company decisions.
Work alongside Capacity, TI and DC planning to anticipate capacity constraints and implement efficiency gains that improve unit economics and overall Profit and Loss (P&L).
Develop robust P&L and Margin models to articulate margin drivers to the executive leadership.
Develop NPV and cash flow models to evaluate profitability for future NPI platforms and benchmark against other competitive products.
Senior Financial Analyst, Search and Maps, Marketing Finance
Security Engineer on DeepMind Agentic Detection and Response in New York, responsible for operational and engineering tasks in AI-powered detection engineering and security operations.
Partner closely with Engineering, Research Data Science, UX, Go-To-Market (GPS/GPL), Legal, and Privacy teams to align incentives across horizontal infrastructure and vertical ad channels
Engage directly with advertisers, Sales, and gTech to diagnose complex attribution behaviors, design causal validation frameworks for Last-Click opt-out cohorts, and build customer trust in AI-driven measurement
Partner with regional product leads, Sales, and gTech Engagement Managers to assess customer marketing objectives, technical maturity, infrastructure, and first-party data management strategies.
Lead technical consultations and martech diagnostic sessions to uncover opportunities for custom solutions, ensuring designs respect industry-specific data constraints and business cycles.
Translate complex customer requirements into clear system architectures and technical specifications that prioritize scalability, reusability, and media activation.
Lead technical handovers to the engineering team by authoring high-quality, prototype-grounded Business/Product Requirement Documents aligned with the product roadmap.
Serve as the entry gatekeeper to the Engineering CoE.
Requirements
Bachelor’s degree or equivalent practical experience
Nice to have: Master’s degree in Business, Statistics, Mathematics, Economics, Engineering or Applied Science
Nice to have: Experience with Google Ads, Google Marketing Platform products (e.g., SA360, DV360, GA4)
Nice to have: Experience with Google Cloud services
Partner with Engineering, TI, and PM to analyze the performance and Total Cost of Ownership (TCO) for AI Product SKUs, incorporating these insights into customer proposals.
Partner with Cloud Product, Capacity and Engineering on various efficiency initiatives to utilize infra and develop next year efficiency targets.
Requirements
Bachelor's degree in Business, Finance, Economics, Statistics, or another quantitative field, or equivalent practical experience.
Nice to have: Deep knowledge of Cloud infrastructure
Nice to have: AI/ML hardware
Nice to have: streamlining complex planning cycles
Nice to have: balancing free cash flow with long-term strategic priorities
Partner Solutions Architect, Ecosystem Engineer Data SystemsNewGoogle · Atlanta, US+5 more