Data Analytics Customer Engineer, Google Cloud (English)
Google · Posted Oct 13
Search engine, cloud computing, software, hardware, and artificial intelligence services
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About the role
Google Cloud delivers enterprise-grade solutions that leverage Google's technology to help organizations digitally transform, serving customers in more than 200 countries and territories. The Agentic Data Cloud team focuses on modern open lakehouse architectures, data and AI pipelines, and unified data foundations that power conversational AI. As an Agentic Data Cloud Customer Engineer, this role acts as the technical subject matter expert partnering with Sales Specialists on pre-sales strategy, designing and deploying production-grade Data + AI pipelines, and advising customer executives on migrations to Google Cloud Platform.
What you will do
- Define technical strategy for large accounts, engaging C-level executives via live demonstrations to solve business problems using the Agentic Data Cloud.
- Design, code, and deploy production-grade Data + AI pipelines (e.g., fraud detection, recommendation engines) and map legacy data estates to open-format architectures (Apache Iceberg).
- Orchestrate Intent-Driven data engineering to autonomously deploy PySpark pipelines using the Data Agent Kit, Antigravity, and Model Context Protocol.
- Lead high-impact showcases and technical value validations using BigQuery, Borderless Lakehouse, Knowledge Catalog, Spark, and Vertex AI to prove business outcomes.
- Conduct detailed Total Cost of Ownership (TCO) analyses and optimize architectures (such as balancing DRAM/SSD, compute shapes, and token spend) to prevent runaway costs on the Lightning Engine.
Skills used in this role
Preferred qualifications
- Experience designing and deploying enterprise Retrieval-Augmented Generation (RAG) pipelines, Large Language Model (LLM) application integrations, or context orchestration frameworks.
- Experience implementing enterprise data/AI governance, metadata management, access control, or lineage tracking across modern catalogs.
- Experience with developer advocacy, building internal technical programs, delivering technical enablement, or contributing to open-source data/AI communities.
- Experience in core data science workflows, including proficiency with data manipulation libraries and integrating data pipelines with ML platforms.
- Experience applying value-selling principles to align technical architectures with business outcomes.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Google
Google LLC is an American multinational technology company focusing on artificial intelligence, online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, and consumer electronics. As a subsidiary of Alphabet Inc., it is widely recognized for services like Google Search, YouTube, Android, and the Gemini AI ecosystem.
- Industry
- Internet
- Company size
- 180000+ employees
- Founded
- 1998-09-04
- Location
- Mountain View, California, USA
- Funding stage
- Public Company
Funding
Public Company · $25M raised
- 1999-06-07Series A$25M
Leadership
Chief Executive Officer
Senior Vice President and Chief Financial Officer
Senior Vice President and Chief Business Officer
Chief Executive Officer, Google Cloud
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