Role Description
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Atlanta, GA, USA; Austin, TX, USA; Addison, TX, USA; Miami, FL, USA; Raleigh, NC, USA; Durham, NC, USA; Reston, VA, USA.### 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 in pre-sales or field engineering at an enterprise technology company, or similar customer-facing experience.
- Ability to travel up to 25% to customer sites.
Preferred qualifications:
- Technical sales experience or professional consulting experience in the fields of cloud computing, data analytics, information lifecycle management, and Big Data.
- People management experience leading technical sales or consulting teams for Cloud Computing or Data Analytics products and platforms.
- Experience influencing cross-functional teams (e.g., Product Management, Engineering, Sales), customers, and partners to impact business goals, customer experience, and customer expansion.
- Thought leader in Data Analytics and adjacent practice areas, specialized in technical sales and strategies around holistic customer and industry solutions.
About the job -----------------
As a Customer Engineering (CE) Manager, you lead and deploy a team of subject matter experts responsible for working alongside our customers to provide trusted technical and solution advice to accelerate workload migration and remove technical blockers. You will foster a culture of technical ownership and understand the mechanics of architecture, delivery, and consumption across the Google Cloud portfolio.
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, ensuring customer needs are represented in product roadmaps and new technology is incubated and scaled. * 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. * Lead and own high impact customer C-level or ITDM relationships who make or influence Data and AI enterprise technology decisions. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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