Agentic Data Cloud Engineer - Enterprise Data & AI

Google; New York (NY); On-site; USD 127,000 - 184,000; Full time

Benefits offered by this job

Bonus target

Equity

Benefits

Job summary

Google is seeking an Agentic Data Cloud Customer Engineer II to partner with Sales and act as the trusted technical advisor for customers in the Google Cloud ecosystem. This role maps complex legacy data estates and champions migrations to GCP, building end-to-end Data + AI pipelines and showcasing modern lakehouse architectures through live demonstrations.

Ideal candidates have deep Python and PySpark expertise, experience with data platforms and governance, and can translate technical

Qualifications

• 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.

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 and map legacy data estates to open-format architectures (Apache Iceberg).
• Orchestrate data engineering to deploy PySpark/dbt pipelines using the Data Agent Kit and Model Context Protocol.
• Lead showcases and validate value using BigQuery, Knowledge Catalog, Spark, and Vertex AI to prove business outcomes.
• Conduct TCO analyses and optimize architectures to prevent runaway costs.

Education

Bachelor's degree or equivalent practical experience

Tools

BigQuery

Vertex AI

Apache Iceberg

dbt

Job description

Google is seeking an Agentic Data Cloud Customer Engineer II to partner with Sales and act as the trusted technical advisor for customers in the Google Cloud ecosystem. This role maps complex legacy data estates and champions migrations to GCP, building end-to-end Data + AI pipelines and showcasing modern lakehouse architectures through live demonstrations.

Ideal candidates have deep Python and PySpark expertise, experience with data platforms and governance, and can translate technical