Forward Deployed Engineer, Data, GenAI, Google Cloud

United States Digital Space LLC; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

United States Digital Space LLC is hiring Forward Deployed Engineers (Data and AI) to work with massive enterprise data lakes and warehouses, delivering production-grade AI workflows through BigQuery, Dataflow, Dataform/dbt, and secure code execution sandboxes.

You will embed with the largest customers’ engineering and data teams, driving discovery, pipeline engineering, semantic modeling, evaluation harness setup, and long-term reliability under latency and governance constraints.

Qualifications

• Bachelor’s degree or equivalent practical experience in engineering or CS.
• 5 years of software development and data engineering experience with SQL, Python, Java, Scala, or Go.
• Experience with ETL/ELT frameworks (dbt, Dataform) and designing enterprise data modeling layers or data marts.
• Master’s or PhD is preferred in related technical fields.
• Experience integrating semantic metadata formats into large-scale data warehouses and lakes.
• Deep experience designing batch, offline, and online evaluation harnesses and intelligence mining bets to benchmark capabilities.

Responsibilities

• Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade workflows.
• Co-build with customer engineering teams to instill company-grade development practices for long-term success.
• Design and build high-throughput batch and streaming data pipelines and utilities to curate multi-terabyte evaluation datasets.
• Construct scalable ETL/ELT pipelines using Dataform, dbt, BigQuery, or Dataproc to design enterprise data marts and semantic models.
• Create mechanisms for large-scale synthetic data generation while maintaining referential integrity across complex schemas.

Skills

SQL

Python

Java/Scala/Go

ETL/ELT frameworks

Data modeling / data marts

BigQuery / Dataproc

Synthetic data generation

Secure code execution sandboxes

Semantic metadata / ontologies

Education

Bachelor’s degree in Engineering/CS/related field

Master’s degree or PhD in CS/Data Science/AI

Tools

dbt

Dataform

BigQuery

Dataproc

Job description

the company will be prioritizing applicants who have a current right to work in Singapore, and do not require the company's sponsorship of a visa.

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 5 years of experience with software development and data engineering with SQL, Python, Java, Scala, or Go.
• Experience with Extract, Transform, Load/Extract, Load, Transform (ETL/ELT) frameworks (e.g., dbt, Dataform) and designing enterprise data modeling layers or data marts.

Preferred qualifications:

• Master's degree or PhD in Computer Science, Data Science, Artificial Intelligence, or a related technical field.
• Experience integrating semantic metadata formats enterprise taxonomies, or ontologies into large-scale data warehouses and lakes.
• Deep experience designing batch, offline, and online evaluation harnesses and intelligence mining jobs to benchmark LLM capabilities (e.g., Text-to-SQL accuracy, semantic parsing, etc).
• Advanced expertise in synthetic data generation at scale while maintaining multi-table referential integrity using tools like Faker, Snowfakery, or custom constraint engines.
• Practical knowledge of configuring and deploying secure code execution harnesses and interpreter sandboxes (e.g., Python/SQL execution environments) for automated data analysis.

About the job

We build frontier models and foundational data platforms.

As a Forward Deployed Engineers (Data and AI) you will work seamlessly over massive, complex enterprise data lakes, warehouses, and transactional systems in production, under real latency, throughput, and governance constraints. You will embed with the engineering and data architecture organizations of the largest customers to take the company's enterprise data and AI stack BigQuery, Dataproc, Dataflow, Dataform/dbt, Gemini for Data, and code execution sandboxes, from architectural whiteboard to high-throughput, production-grade workflows. You will identify what slows a 25,000-engineer enterprise down when deploying Text-to-SQL, automated evaluations, and data intelligence workflows, design the data systems that fix it, and own them end-to-end: discovery, pipeline engineering, semantic data modeling, evaluation harness setup, rollout, and long-tail reliability.

It's an exciting time to join the company Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll succeed by leveraging the company'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

• Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows that drive measurable Return on Investment (ROI).
• Co-build with customer engineering teams to instill the company-grade development best practices, ensuring long-term project success and high end-user adoption.
• Design and build high-throughput batch and streaming data pipelines and utilities to curate multi-terabyte evaluation datasets and execute offline/online evaluation generation jobs for model intelligence mining.
• Construct scalable ETL/ELT pipelines using Dataform, dbt, BigQuery, or Dataproc to design enterprise data marts and semantic modeling layers specifically engineered to maximize data quality, schema clarity, and accuracy for Text-to-SQL and natural language analytical interfaces.
• Create mechanisms for large-scale synthetic data generation that maintain strict referential integrity across complex relational schemas, leveraging advanced tools and custom generative utilities for privacy-safe model benchmarking and fine-tuning.

the company 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 the company's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.