Senior Agentic Data Cloud Engineer – Data & AI Architect

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

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

Paid time off 20 days/year

Sick time 40 hours/year

Maternity leave 28-30 weeks

Baby Bonding leave 18 weeks

13 paid holidays

Job summary

Google LLC in Mountain View, CA is seeking an Agentic Data Cloud Customer Engineer to lead technical pre-sales for large accounts. You will map complex data estates and migrate to open lakehouse architectures using PySpark, BigQuery, and AI pipelines.

Preferred expertise includes enterprise data governance, cost optimization, and translating architecture into business value for CDOs and CTOs.

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.
• Experience with data programming languages and leveraging agentic platforms.

Responsibilities

• Define technical strategy for large accounts, engaging executives with live demos.
• Design, code, and deploy production-grade Data and AI pipelines and map legacy estates.
• Orchestrate data engineering to deploy PySpark/dbt pipelines with specialized tools.
• Lead showcases and value validations using BigQuery, Spark, and Vertex AI.
• Conduct detailed TCO analyses and optimize architectures to control costs.

Skills

Python

PySpark

Data pipelines

Data lakes

Education

Bachelor's degree or equivalent practical experience

Tools

BigQuery

dbt

Apache Iceberg

Knowledge Catalog

Job description

Google LLC in Mountain View, CA is seeking an Agentic Data Cloud Customer Engineer to lead technical pre-sales for large accounts. You will map complex data estates and migrate to open lakehouse architectures using PySpark, BigQuery, and AI pipelines.

Preferred expertise includes enterprise data governance, cost optimization, and translating architecture into business value for CDOs and CTOs.