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About the Role
As an Agentic Data Cloud Customer Engineer, you will be a premier technical subject matter expert, partnering with Sales Specialists to execute the technical pre-sales strategy for customers. You will serve as a trusted technical advisor to CDOs, CTOs, Lead Architects, and developers, leading proactive discoveries to map complex, legacy customer data estates and qualify them for migration to GCP. You are a builder and architect who designs, codes, and deploys production-grade, end-to-end Data + AI pipelines to solve real-world enterprise problems. You will whiteboard modern open lakehouse architectures and run code demonstrations showing how unified data foundations power deterministic, hallucination-free conversational AI. Leveraging value-selling, you will conduct Total Cost of Ownership analyses and optimize architectures to prevent runaway spend, helping customers adopt modern data engineering practices that securely unify data, analytics, and AI.
Responsibilities
- 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/dbt pipelines using the Data Agent Kit, Antigravity, and Model Context Protocol.
- Lead showcases and technical value validations using BigQuery, Borderless Lakehouse, Knowledge Catalog, Spark, and Vertex AI to prove business outcomes.
- Conduct detailed TCO analyses and optimize architectures (such as balancing DRAM/SSD, compute shapes, and token spend) to prevent runaway costs on the Lightning Engine.
Requirements
- Bachelor's degree or equivalent practical experience.
- 6 years of experience as a data or systems engineer, solutions architect, or pre-sales consultant.
- Experience delivering demos, workshops, or architect overviews to business leaders.
- Experience migrating, refactoring, or debugging proprietary or open source workloads.
- Experience building data platforms, warehouses, or data lakes.
- Experience with data programming languages and leveraging agentic platforms.
- Ability to communicate in English fluently to manage stakeholder relationships.
- Experience designing and deploying enterprise Retrieval-Augmented Generation (RAG) pipelines, LLM application integrations, or context orchestration frameworks.
- Practical experience implementing enterprise data/AI governance, metadata management, access control, or lineage tracking across modern catalogs.
- Experience with developer advocacy, building internal technical advocate 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.
Skills
- Python
- PySpark
- distributed data systems
- data programming languages
- agentic platforms
- Retrieval-Augmented Generation (RAG) pipelines
- LLM application integrations
- context orchestration frameworks
- data/AI governance
- metadata management
- access control
- lineage tracking
- developer advocacy
- technical enablement
- data manipulation libraries
- ML platforms
- value-selling principles
Experience Level
- 6 years of experience
Education Level
- Bachelor's degree or equivalent practical experience
Salary/Compensations
- $127000 - $184000 (USD) + 42.86% bonus target + equity
Benefits
- equity
- benefits
About the Company
- Google Cloud accelerates every organization’s ability to digitally transform its business and industry.
- We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably.
- Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Equal Opportunity
- Individual pay is determined by factors including job-related skills, experience, and relevant education or training.