Senior GenAI Data Engineer — Cloud Pipelines & AI

Google; Singapore; On-site; SGD 180,000 - 290,000; Full time

Job summary

Google in Singapore is seeking Forward Deployed Engineers (Data and AI) to work with massive enterprise data lakes and warehouses, translating architecture into production-grade pipelines. You will embed with Google’s data stack—from BigQuery to Dataform/dbt—and drive end-to-end discovery, pipeline engineering, and semantic data modeling.

The role focuses on high-throughput batch/streaming pipelines and synthetic data generation while ensuring data integrity across complex schemas for

Qualifications

• Bachelor’s degree in Engineering, Computer Science, or related field, or equivalent practical experience.
• 8 years of software development and data engineering experience with SQL, Python, Java, Scala, or Go.
• Experience with ETL/ELT frameworks and enterprise data modeling layers or data marts.

Responsibilities

• Serve as a developer for complex AI applications, transitioning prototypes to production-grade workflows.
• Co-build with customer teams to ensure Google-grade development practices and long-term success.
• Design and build high-throughput batch and streaming data pipelines and curate large evaluation datasets.
• Construct ETL/ELT pipelines with Dataform, dbt, BigQuery, or Dataproc for enterprise data marts and semantic layers.
• Create mechanisms for large-scale synthetic data generation while maintaining referential integrity.

Skills

SQL

Python

Data modeling

Education

Bachelor's degree or equivalent

Tools

dbt

Dataform

BigQuery

Dataproc

Job description

Google in Singapore is seeking Forward Deployed Engineers (Data and AI) to work with massive enterprise data lakes and warehouses, translating architecture into production-grade pipelines. You will embed with Google’s data stack—from BigQuery to Dataform/dbt—and drive end-to-end discovery, pipeline engineering, and semantic data modeling.

The role focuses on high-throughput batch/streaming pipelines and synthetic data generation while ensuring data integrity across complex schemas for