Senior Data Analytics Cloud Engineer — FSI

Google

Chicago (IL)

On-site

USD 152,000 - 221,000

Full time

2 days ago

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Job summary

Google Cloud is seeking a Practice Customer Engineer specializing in Agentic Data Cloud. You will partner with Sales to differentiate Google Cloud and position data platforms as the foundation for enterprise-grade Agentic workflows.

You will lead as the technical authority to accelerate wins, remove blockers, and drive adoption of data and AI workloads. You will design unified data foundations, build production-grade prototypes, and advocate Google’s data tools like BigQuery and Lakehouse,

Qualifications

Bachelor's degree or equivalent practical experience.
10 years of experience with cloud native architecture in a customer-facing or support role.
Experience with Big Data technologies or concepts (analytics warehousing, data processing, data governance, ETL/ELT, SQL, Spark).
Experience using programming languages (e.g., Python, Spark, SQL) to demo, prototype, or workshop with customers.
Experience presenting to technical stakeholders and executive leaders on cataloging, access controls, and lineage for AI and agentic applications.

Responsibilities

Drive the technical win for complex workloads within Data Analytics to ensure rapid and successful adoption, primarily supporting the sales cycle from use case identification, technical evaluation, and through customer ramp.
Combine sales strategies and direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
Deliver critical feedback from customer engagements to Product and Engineering teams to improve architectures and solutions, working within their management systems to document, prioritize and drive resolution of customer feature requests and issues, while leveraging learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team.
Help Enterprise customers leverage industry-specific unified data foundations to power real-time, AI-driven experiences (including predictive analytics, generative AI, and agent-driven applications), with clear strategic and technical differentiated solutions that directly address technical bottlenecks.