Agentic Data Cloud Customer Engineer, Startups, Google Cloud
Overview:
As the premier technical expert in your territory, you partner with sales to guide pre-sales strategy and act as a trusted advisor to C-level data leaders. You design, code, and deploy end-to-end data and AI pipelines that solve real-world enterprise problems, and you demonstrate modern lakehouse architectures with live code to show concrete business value. You map complex legacy estates to open architectures and optimize costs to prevent runaway spend. This role blends hands-on engineering with strategic storytelling to drive customer outcomes on Google Cloud. Compensation / Benefitsbonus targetequitybenefitsrelocation optionscampus location (Playa Vista)
Responsibilities:
- Define technical strategy for large accounts and engage C-level executives through live demonstrations
- Design, code, and deploy production-grade data + AI pipelines and map legacy data estates to open-format architectures (Iceberg)
- Orchestrate intent-driven data engineering to autonomously deploy PySpark/dbt pipelines using agentic tools
- Lead high-impact showcases and validate technical value using BigQuery, Borderless Lakehouse, Knowledge Catalog, Spark, and Vertex AIConduct detailed TCO analyses and optimize architectures to control costs on the lightning engine
- Partner with sales to execute pre-sales strategy and qualify migrations to Google Cloud Platform (GCP)
- Whiteboard modern open lakehouse architectures and demonstrate deterministic, hallucination-free conversational AITranslate technical excellence into business-transforming migrations and data engineering practices
- Drive adoption of modern data governance, data platforms, and AI practices across customers
Key requirements:
- Bachelor's degree or equivalent practical experience 10 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, and experience with data programming languages and leveraging agentic platforms
- Effective communication with executive stakeholders
- Proactive leadership and collaboration with cross-functional teams
- Technical storytelling and enablement for customers
- PythonPySparkdistributed data systems