Data Cloud Frontline Engineer - Production ML Pipelines

Google LLC; 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

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