Enterprise Data Cloud Solutions Architect II

Google

Austin (TX)

On-site

USD 127,000 - 184,000

Full time

5 days ago

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Benefits offered by this job

Health/Dental/Vision/Life/Disability

401(k) with company match

PTO 20 days/year

Sick time 40 hours/year (+ Seattle 69)

Maternity/Baby bonding: 28-30 weeks

Baby Bonding Leave 18 weeks

Holidays 13 days/year

Job summary

Google Cloud seeks an Agentic Data Cloud Customer Engineer to be the premier technical advisor in their territory. You will partner with Sales Specialists to execute the technical pre-sales strategy for customers, serving as the trusted technical advisor to C-levels, Lead Architects, and Developers.

You will lead proactive discoveries to map complex, legacy customer data estates and qualify them for migration to GCP.

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.
Experience building data platforms, warehouses, or data lakes, and experience with data programming languages and leveraging agentic platforms.

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 and 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 high-impact 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.