Forward Deployed Engineering Manager II, Data Cloud

On-site in London·Added today (last checked 13 Nov)

Google

223 open roles

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Our summary

Work mode: On-site, London
Experience: 8+ years

Skills

Requirements

What we're looking for

Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience in cloud computing, technical sales engineering, or software engineering with cloud-native architectures.
2 years of experience managing a software engineering, FDE, or similar technical customer-facing team in a cloud computing environment.
Experience reviewing designs and code in Python, PySpark and SQL.
Experience designing platforms built on Data Cloud services (e.g., BigQuery, Managed Spark / Lightning Engine, Apache Iceberg (Borderless Lakehouse), Spanner, AlloyDB, Pub/Sub, Dataflow, Kafka).
Experience building agentic AI systems on enterprise data (agents, retrieval, vector search, evaluation).

Nice to have

Experience leading forward deployed engineering, field engineering or professional services organizations at a data platform or AI-first company or a hyperscaler’s data and machine learning services team.
Experience engaging credibly with multi-level executives and with engineers.
Experience with Google Cloud data products, or competing against them.
Experience across a broad range of data cloud specializations, including data engineering, data science/machine learning, application development, operations, and analytical databases/data management.
Experience building end-to-end data pipelines, engineering features, and training/deploying machine learning models.
Experience with RAG architectures, chunking/indexing strategies, vector databases, hybrid search, and the use of data governance for grounding agents in enterprise context.

Pay & benefits

What you'll get

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Poland: zł640000 - zł655000 (PLN) + 25% bonus target + equity + benefits

Learn more about benefits at Google. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: London, UK; Warsaw, Poland.

The role

Google Cloud's Data Cloud team builds the data platform behind Google's agentic AI offerings: BigQuery, Managed Spark, borderless Lakehouse, Spanner, AlloyDB and Knowledge Catalog, integrated with Gemini Enterprise.

As a Forward Deployed Engineering Manager, you will lead a Forward Deployed Engineering (FDE) team for Google Cloud's Data Cloud. Your team will bridge the gap between frontier data solutions and production-grade reality for customers. They will take customers data and machine learning workloads from prototype to production on BigQuery, Managed Spark, borderless Lakehouse, Spanner, AlloyDB and Knowledge Catalog. You are a technical leader first: credible with Chief Technology Officers (CTOs) and data platform leaders, able to review your team's designs and code, and a strong judge of engineering talent.

It's an exciting time to join Google Cloud's Go-To-Market team, leading the AI revolution for businesses worldwide. You'll excel by leveraging Google's brand credibility-a legacy built on inventing foundational technologies and proven at scale. We'll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We're a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era-the market is yours.

What you'll do

Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
Partner with sales and tech leadership to define requirements for high-value opportunities, deploying specialized experts to key accounts.
Lead technical hiring for FDE, evaluating data engineering expertise, systems engineering, and coding skills to build an exceptional engineering team.
Identify skill gaps in emerging tech (MCP, tool-calling, and foundation models, building agents), ensuring the team maintains subject matter expertise in an evolving data stack.
Collaborate with product and engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.