Forward Deployed Engineer III, Data Cloud, Google Cloud (English, Spanish)

Google; Ciudad de México; On-site; MXN 1,200,000 - 1,800,000; Full time

Job summary

Google Cloud’s Data Cloud team builds the data platform behind Google’s agentic AI offerings: BigQuery, Managed Spark, lakehouse, Spanner, AlloyDB and Knowledge Catalog, integrated with Gemini Enterprise. As a Forward Deployed Engineer 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.

You will deploy complex systems and feed field insights back into Google Cloud’s roadmap, collaborating across

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, AlloyDB).
• Experience taking production-grade data cloud solutions from conception to launch, architecting data systems on cloud platforms (GCP), and building structured/unstructured pipelines.
• Experience training, evaluating, and deploying machine learning models in production.
• Ability to communicate in English and Spanish fluently to collaborate with regional teams.

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.

Skills

Python

SQL

Software engineering

Data engineering

Solution architecture

Machine learning

Education

Bachelor’s degree in Engineering/Computer Science

Tools

BigQuery

Spanner

AlloyDB

PySpark

Spark

Dataplex

Job description

• 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, AlloyDB).
• Experience taking production-grade data cloud solutions from conception to launch, architecting data systems on cloud platforms (GCP), and building structured/unstructured pipelines.
• Experience training, evaluating, and deploying machine learning models in production.
• Ability to communicate in English and Spanish fluently to collaborate with regional teams.

Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.

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

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 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.

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.

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 also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

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.

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.