Customer Engineer III, Data Analytics, FSI, Google Cloud
Summary
Pre-sales Customer Engineer at Google Cloud partnering with sales to win Financial Services customers by designing unified data architectures, building prototypes, and demoing BigQuery, data governance, and agentic AI capabilities. Needs 10 years of cloud architecture experience plus Big Data and Python/SQL skills.
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You address and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
As a Practice Customer Engineer specializing in Agentic Data Cloud, you will partner with Sales Specialist to differentiate Google Cloud and position data platform as the primary foundation for enterprise-grade Agentic workflows. You will serve as the technical authority responsible for accelerating technical wins, removing complex architectural blockers, and driving the adoption of specialized, mission-critical data and AI workloads. In this role, you will leverage deep domain expertise to design unified data foundation architectures and build production-grade prototypes and Minimum Viable Products. You will advocate Google Cloud's data suite, including BigQuery, Knowledge Catalog, and the Borderless Lakehouse demonstrating how Lakehouse scale, semantic cataloging, and automated data governance directly empower high-quality, trustworthy AI Agents.
In this role, you will bridge modern data architectures with real-time, agentic execution, enable customers to move from static analytics to autonomous, AI-driven experiences.You will collaborate with technical counterparts to shape customer cloud strategies, solve sophisticated data-engineering challenges, and provide a critical feedback loop directly to Product Engineering to influence roadmap development. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $152000 - $221000 (USD) + 42.86% bonus target + equity + benefits
Learn more about benefits at Google.
As a Practice Customer Engineer specializing in Agentic Data Cloud, you will partner with Sales Specialist to differentiate Google Cloud and position data platform as the primary foundation for enterprise-grade Agentic workflows. You will serve as the technical authority responsible for accelerating technical wins, removing complex architectural blockers, and driving the adoption of specialized, mission-critical data and AI workloads. In this role, you will leverage deep domain expertise to design unified data foundation architectures and build production-grade prototypes and Minimum Viable Products. You will advocate Google Cloud's data suite, including BigQuery, Knowledge Catalog, and the Borderless Lakehouse demonstrating how Lakehouse scale, semantic cataloging, and automated data governance directly empower high-quality, trustworthy AI Agents.
In this role, you will bridge modern data architectures with real-time, agentic execution, enable customers to move from static analytics to autonomous, AI-driven experiences.You will collaborate with technical counterparts to shape customer cloud strategies, solve sophisticated data-engineering challenges, and provide a critical feedback loop directly to Product Engineering to influence roadmap development. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $152000 - $221000 (USD) + 42.86% bonus target + equity + benefits
Learn more about benefits at Google.
- 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.
Minimum 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 (e.g., analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, Spark, performance or scalability optimizations, batch versus streaming).
- 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.
Preferred qualifications:
- Experience in technical sales or consulting in cloud computing, data analytics, and Big Data.
- Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures.
- Experience with architecture design, implementing, tuning, schema design, and query optimization of scalable and distributed systems.
- Experience with cloud computing (e.g., infrastructure, storage, platforms, data) and the cloud market, engaged dynamics, and customer buying behavior.
- Experience understanding customer requirements with the ability to break down requirements and design technical architectures.