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Forward Deployed Engineer III, Data Cloud, Google Cloud

Pay
USD 174,000–252,000/yearAnnual period assumed — pay source
As a Forward Deployed Engineer (FDE) on our Data Cloud team, you will be an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. By embedding with accounts, you will serve a dual purpose: providing "white glove" deployment of complex systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .
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Before you apply

Employer’s visa record
10,916 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.

What you’ll work on

Full posting
  • Build and performance-tune PySpark, SQL and Python workloads on BigQuery and Spanner

  • Stand up working proofs using customers' data, including de-identifying sensitive data

  • Build data foundations for agentic solutions, including lakehouse and access controls

  • Train, evaluate and deploy ML and agentic components with monitoring in place

  • Migrate high-cost analytics, Spark and database workloads onto Google Cloud

From the employer’s posting
Build and ship production data and machine learning workloads with customers, writing, testing, and performance-tuning PySpark, SQL, and Python on BigQuery, Managed Spark, Spanner, and AlloyDB.
Stand up working proofs with customers’ data, including de-identifying sensitive data (e.g., PCI, PHI).
Build the data foundation for agentic solutions, including lakehouse architectures, metadata and semantic context, and the access controls that let custom agents act on trusted data.
Train, evaluate, and deploy machine learning and agentic components where they improve the customer’s business metric, with evaluation and monitoring in place.
Refactor and migrate high-cost analytics, Spark, and operational database workloads from other platforms onto Google Cloud engines, with measured price-performance results.
Education & alternatives
**Minimum qualifications:** + Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. + 5 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including experience writing code in Python and SQL.
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Posting record

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Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 7, 20266 days ago
Recorded sightings
5
Last seen by us
Nov 13, 2026

We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 6

Similar jobs usually come down between day 4 and day 77.

Well past Google’s usual: its jobs come down by about day 3.

From 51 similar postings that came down, and 484 of Google’s. Coming down is not always a hire.

Google is hiring

246 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 6% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • BigQuery
  • Databricks
  • Delta Lake
  • GCP
  • Iceberg
  • Snowflake
  • Spark
  • PySpark
  • React
Where the posting names them
+ Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. + 5 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including experience writing code in Python and SQL. + Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Catalog, and AlloyDB).
**Responsibilities** + Build and ship production data and machine learning workloads with customers, writing, testing, and performance-tuning PySpark, SQL, and Python on BigQuery, Managed Spark, Spanner, and AlloyDB. + Stand up working proofs with customers’ data, including de-identifying sensitive data (e.g., PCI, PHI).
+ 5 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including experience writing code in Python and SQL. + Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Catalog, and AlloyDB). + Experience taking production-grade data cloud solutions from conception to launch, including architecting data systems on cloud platforms (e.g., GCP) and building structured/unstructured pipelines.
+ Experience building LLM applications (e.g., Gemini, RAG, vector search) and multi-agent frameworks (LangGraph, CrewAI, ADK) using advanced patterns (ReAct, delegation). + Experience with GCP data products (BigQuery, Spark, Spanner, Dataplex) or equivalents (Databricks, Snowflake), and open table formats (Iceberg, Delta Lake). + Experience migrating analytics, Spark, or database workloads between platforms with measured cost and performance outcomes.
Forward Deployed Engineer III, Data Cloud, Google Cloud Share Forward Deployed Engineer III, Data Cloud, Google Cloud
Forward Deployed Engineer III, Data Cloud, Google Cloud Share Forward Deployed Engineer III, Data Cloud, Google Cloud _corporate_fare_ Google _place_ San Francisco, CA, USA; Austin, TX, USA; +6 more; +5 more
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Forward Deployed Engineer III, Data Cloud, Google Cloud _info_outline_
+ Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Catalog, and AlloyDB). + Experience taking production-grade data cloud solutions from conception to launch, including architecting data systems on cloud platforms (e.g., GCP) and building structured/unstructured pipelines. + Experience training, evaluating, and deploying machine learning models in production.
**About the job** As a Forward Deployed Engineer (FDE) on our Data Cloud team, you will be an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. By embedding with accounts, you will serve a dual purpose: providing "white glove" deployment of complex systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
+ Train, evaluate, and deploy machine learning and agentic components where they improve the customer’s business metric, with evaluation and monitoring in place. + Refactor and migrate high-cost analytics, Spark, and operational database workloads from other platforms onto Google Cloud engines, with measured price-performance results. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
**Preferred qualifications:** + Experience building LLM applications (e.g., Gemini, RAG, vector search) and multi-agent frameworks (LangGraph, CrewAI, ADK) using advanced patterns (ReAct, delegation). + Experience with GCP data products (BigQuery, Spark, Spanner, Dataplex) or equivalents (Databricks, Snowflake), and open table formats (Iceberg, Delta Lake).

Your next step

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Already applied? Track this application

Has Google posted this job before?

Yes. We’ve followed 6 other Forward Deployed Engineer III, Data Cloud, Google Cloud jobs there since November 2026. All 6 are still up.

  1. KirklandStill up after 7 days, first seen Nov 7
  2. New YorkStill up after 7 days, first seen Nov 7
  3. AustinStill up after 7 days, first seen Nov 7
  4. San FranciscoStill up after 7 days, first seen Nov 7
  5. ChicagoStill up after 7 days, first seen Nov 7
  6. SeattleStill up after 7 days, first seen Nov 7
  7. This jobUp 7 days so far, first seen Nov 7

Large employers often post one title for several teams, so these can be separate openings.

About Google

People
About 190,820 in 2025, up 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as GOOGL.
H-1B visas
1,765 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

Forward Deployed Engineer III, Data Cloud, Google Cloud Share Forward Deployed Engineer III, Data Cloud, Google Cloud _corporate_fare_ Google _place_ San Francisco, CA, USA; Austin, TX, USA; +6 more; +5 more **Mid** Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. Share Forward Deployed Engineer III, Data Cloud, Google Cloud _info_outline_ XIn most instances, this position requires in-person interviews as part of the hiring process. Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act. In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: + Health, dental, vision, life, disability insurance + Retirement Benefits: 401(k) with company match + Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment + Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance + Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks + Baby Bonding Leave: 18 weeks + Holidays: 13 paid days per year Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **San Francisco, CA, USA; Austin, TX, USA; Chicago, IL, USA; Kirkland, WA, USA; New York, NY, USA; Seattle, WA, USA; Sunnyvale, CA, USA** . **Minimum qualifications:** + Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. + 5 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including experience writing code in Python and SQL. + Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Catalog, and AlloyDB). + Experience taking production-grade data cloud solutions from conception to launch, including architecting data systems on cloud platforms (e.g., GCP) and building structured/unstructured pipelines. + Experience training, evaluating, and deploying machine learning models in production. **Preferred qualifications:** + Experience building LLM applications (e.g., Gemini, RAG, vector search) and multi-agent frameworks (LangGraph, CrewAI, ADK) using advanced patterns (ReAct, delegation). + Experience with GCP data products (BigQuery, Spark, Spanner, Dataplex) or equivalents (Databricks, Snowflake), and open table formats (Iceberg, Delta Lake). + Experience migrating analytics, Spark, or database workloads between platforms with measured cost and performance outcomes. + Skilled in prompt engineering, model evaluation, LLM-native metrics (latency, tokens/sec, cost), state management, and granular tracing. **About the job** As a Forward Deployed Engineer (FDE) on our Data Cloud team, you will be an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. By embedding with accounts, you will serve a dual purpose: providing "white glove" deployment of complex systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) . **Responsibilities** + Build and ship production data and machine learning workloads with customers, writing, testing, and performance-tuning PySpark, SQL, and Python on BigQuery, Managed Spark, Spanner, and AlloyDB. + Stand up working proofs with customers’ data, including de-identifying sensitive data (e.g., PCI, PHI). + Build the data foundation for agentic solutions, including lakehouse architectures, metadata and semantic context, and the access controls that let custom agents act on trusted data. + Train, evaluate, and deploy machine learning and agentic components where they improve the customer’s business metric, with evaluation and monitoring in place. + Refactor and migrate high-cost analytics, Spark, and operational database workloads from other platforms onto Google Cloud engines, with measured price-performance results. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) . Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC\_KnowYourRights\_10\_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) . If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right. 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 https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.
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