Forward Deployed Engineer III, Data Cloud, Google Cloud

Google; Singapore; Presencial; SGD 140.000 - 210.000; Tempo integral

Resumo da vaga

Google Cloud’s Data Cloud team seeks a Forward Deployed Engineer to embed with customers, moving data and ML workloads from idea to production on Google Cloud.

You will build data foundations and agentic solutions using PySpark, SQL, and Python across BigQuery, Spanner, and AlloyDB, while ensuring data privacy and governance. This role blends engineering with customer-facing impact.

Qualificações

• Bachelor's degree in Engineering, CS, or related field, or equivalent practical experience.
• 5 years of experience in software/data engineering, solution architecture, ML, or consulting, with Python and SQL.
• Experience with data cloud ecosystem products/technologies (Spark, PySpark, BigQuery, Spanner, Data Catalog, AlloyDB).
• Experience taking production-grade data cloud solutions from conception to launch on cloud platforms (GCP) and building data pipelines.
• Experience training, evaluating, and deploying machine learning models in production.

Responsabilidades

• Build and ship production data and ML workloads with customers using PySpark, SQL and Python on BigQuery, Managed Spark, Spanner and AlloyDB.
• Present working proofs with customers’ data, including de-identifying sensitive data (PCI, PHI).
• Build data foundations for agentic solutions, lakehouse architectures, metadata, semantic context, and access controls.
• Train, evaluate and deploy ML and agentic components to improve business metrics with monitoring.
• Refactor and migrate high-cost analytics and Spark workloads to Google Cloud with measured price-performance results.

Conhecimentos

Python

SQL

Data engineering

Cloud architecture

ML deployment

Formação

Bachelor's degree in Engineering, Computer Science, or related field (or equivalent practical experience)

Ferramentas

PySpark

BigQuery

Spanner

AlloyDB

Data Catalog

GCP

Descrição da vaga

• 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 coding experience in Python and SQL.


• Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Data 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 implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).


• Experience in prompt developing, model evaluation, and the creative application of AI.


• Experience building applications on large language models (LLM) over enterprise data (e.g., Gemini, agents, RAG, vector search) and evaluating them for quality, latency and cost.


• Experience migrating analytics, Spark or database workloads between platforms with measured cost or performance outcomes.


• Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing 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 the Data Cloud team, you are an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. You will function as an \"innovator-builder,\" working directly within customers’ environments to move data and machine learning workloads from idea to production on Google Cloud, leveraging experience with programming languages (e.g. PySpark, SQL, Python) and the data cloud ecosystem (e.g. BigQuery, Managed Spark, Spanner, AlloyDB). You will build the data foundations that agents depend on, and train and evaluate machine learning models on customer data. By embedding with strategic accounts, you 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.


• Present 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, 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.