Customer Engineering Manager, Data Analytics, FSI, Google Cloud

Google; New York (NY); On-site; USD 192,000 - 267,000; Full time

Job summary

Google is seeking a Customer Engineering Manager in the United States to lead a high-performing Data Analytics team that partners with customers to architect and deploy modern data platforms. You will drive trusted technical advisory, enable complex workload migrations, and translate architectural direction into measurable business outcomes.

You will champion Google Cloud’s Agentic Data Cloud strategy and guide teams to demonstrate governance, semantic cataloging, and lakehouse architectures

Qualifications

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing role.
• 5 years of Experience in pre-sales or field engineering leadership roles at an enterprise technology company, or similar customer-facing experience.
• Experience working in the Financial Services Industry or with Financial Services customers
• Experience pitching a connected story of modern Data & AI foundations to C-level executives (CDOs, CAIOs, CTOs, CIOs, LoBs) for Financial Services use cases with clear business outcomes

Responsibilities

• Lead a team of Data Analytics technical experts in a matrixed organization; focus on talent strategy and skill development.
• Guide regional Data Analytics community to scale contributions and share innovations.
• Influence cross-functional teams and manage high-impact C-level relationships around Data and AI decisions.
• Lead demonstrations/prototypes of Agentic Data Cloud and AI products in customer environments.
• Coach enterprise customers on unified data foundations for real-time, AI-driven experiences and differentiated solutions.

Skills

Cloud native architecture

Customer-facing leadership

Pre-sales leadership

Financial Services experience

C-level storytelling

Education

Bachelor's degree or equivalent

Job description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing role.
• 5 years of Experience in pre-sales or field engineering leadership roles at an enterprise technology company, or similar customer-facing experience.
• Experience working in the Financial Services Industry or with Financial Services customers
• Experience pitching a connected story of modern Data & AI foundations to C-level executives (CDOs, CAIOs, CTOs, CIOs, LoBs) for Financial Services use cases with clear business outcomes

Preferred qualifications:

• Experience as a thought leader in Data Analytics and AI, specialized in technical sales and strategies around holistic customer and industry solutions.
• Experience in technical sales or professional consulting in the fields of cloud computing, data analytics, information lifecycle management, and Big Data.
• Experience in people management leading technical sales or consulting teams for Cloud Computing or Data Analytics products and platforms.
• Experience influencing cross-functional teams, customers, and partners to impact business goals, customer experience, and customer expansion.

About the job

As a Customer Engineering (CE) Manager, you will lead and scale a high-performing team of technical subject matter experts and solutions architects responsible for partnering with customers to architect, validate, and deploy modern data platforms. You will guide your team in providing trusted technical advisory, accelerating complex workload migrations, eliminating technical friction, and turning architectural direction into measurable business outcomes.

In this role, you will advocate Google Cloud’s Agentic Data Cloud strategy, positioning our unified data suite—including BigQuery, Knowledge Catalog, and the Borderless Lakehouse—as the foundational platform powering enterprise-grade, autonomous agentic workflows. You will lead your team to demonstrate how robust data governance, semantic cataloging, and unified lakehouse architectures directly eliminate high-quality, real-time AI agents.
You will foster a culture of deep technical ownership, engineering excellence, and customer empathy. By mastering the mechanics of architecture, delivery, and consumption across Google Cloud’s data and AI portfolio, you will partner closely with Sales leadership and building strong ecosystems of customer relationships and cross-functional partnerships to shape customer transformation roadmaps, multiply organizational impact, and establish Google Cloud as the definitive foundation for the Agentic AI era.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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: $192000 - $267000 (USD) + 42.86% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead a team of Data Analytics technical experts in a matrixed organization. Focus on talent strategy, assessing go-to-market readiness and gaps in CE preparedness, skills development.
• Lead the broader region's Data Analytics technical community, to ensure sub-regional technical contributions, achieve scale through artifact and innovation sharing.
• Influence cross-functional teams, including Product Management and Engineering, lead and own high impact customer C-level or Information Technology Decision Maker (ITDM) relationships who make or influence Data and AI enterprise technology decisions.
• Lead the team to work with Google Cloud Platform to demonstrate and prototype our Agentic Data Cloud and AI products or integrations in customer/partner environments.
• Coach team to guide enterprise customers in leveraging industry-specific unified data foundations to power real-time, AI-driven experiences, with strategic and technical differentiated solutions that address technical bottlenecks.

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