G

Google

Runs Search and YouTube and builds Gemini AI

Forward Deployed Engineering Manager - Data Cloud, Google Cloud

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeTokyo, JapanNo salary listed

About the Job

Requirements

  • A bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • At least 8 years of experience in cloud computing, technical business engineering, or software engineering with cloud-native architectures.
  • At least 2 years of experience managing a software engineering, Forward Deployed Engineering, or related 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 such as BigQuery, Managed Spark/Lightning Engine, Apache Iceberg, Borderless Lakehouse, Spanner, AlloyDB, Pub/Sub, Dataflow, and Kafka.
  • Experience building agentic AI systems on enterprise data, such as agents, retrieval, vector search, and evaluation.

Responsibilities

  • Serve as the technical lead by establishing code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
  • Partner with business and technology leadership to define requirements for high-value opportunities and deploy specialized experts to key accounts.
  • Lead technical hiring for Forward Deployed Engineering by evaluating data engineering expertise, systems engineering, and coding skills.
  • Identify skill gaps in emerging technologies, including Model Context Protocol, tool-calling, and foundation models for building agents, to ensure the team maintains subject matter expertise in an evolving data stack.
  • Collaborate with product and engineering teams to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.
  • Lead a Forward Deployed Engineering team for Google Cloud's Data Cloud.
  • Take customer data and machine learning workloads from prototype to production on BigQuery, managed Spark, borderless Lakehouse, Spanner, AlloyDB, and Knowledge Catalog.
  • Review the team's designs and code and assess engineering talent.

Desired Qualifications

  • 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 executives at multiple levels and with engineers.
  • Experience across a broad range of data cloud specializations, including data engineering, data science and machine learning, application development, operations, and investigative databases and data management.
  • Experience building end-to-end data pipelines, engineering features, and training or deploying machine learning models.
  • Experience with retrieval-augmented generation architectures, chunking and indexing strategies, vector databases, hybrid search, and data governance for grounding agents in enterprise context.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size
10,001+
Company stage
IPO
Headquarters
Mountain View, CA
Founded
1998

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