Agentic Data Cloud Engineer for Startups | AI Pipelines

Google LLC; Los Angeles (CA); On-site; USD 152,000 - 221,000; Full time

Job summary

Google LLC in the Los Angeles area seeks an Agentic Data Cloud Customer Engineer for Startups, Google Cloud. You will be the premier technical advisor, partner with sales to map complex data estates, qualify them for migration to Google Cloud Platform, and design end-to-end data + AI pipelines.

You will lead live demonstrations, push lakehouse architectures, run TCO analyses, and help customers adopt modern data engineering practices.

Qualifications

• 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.

Responsibilities

• Design, code, and deploy production-grade data + AI pipelines.
• Whiteboard lakehouse architectures and run code demonstrations.
• Conduct detailed Total Cost of Ownership (TCO) analyses and optimize architectures to prevent runaway spend.
• Help customers adopt modern data engineering practices that securely unify data, analytics, and AI.
• Translate technical excellence into business-transforming migrations.

Skills

Data engineering

Pre-sales

Demo delivery

Data migration

Python

PySpark

Distributed systems

Education

Bachelor's degree or equivalent practical experience

Tools

BigQuery

Apache Iceberg

Spark

dbt

Vertex AI

Job description

Google LLC in the Los Angeles area seeks an Agentic Data Cloud Customer Engineer for Startups, Google Cloud. You will be the premier technical advisor, partner with sales to map complex data estates, qualify them for migration to Google Cloud Platform, and design end-to-end data + AI pipelines.

You will lead live demonstrations, push lakehouse architectures, run TCO analyses, and help customers adopt modern data engineering practices.