Staff Data Engineer Lead — Scale Real-Time Pipelines & ML

Google DeepMind; Mountain View (CA); On-site; USD 207,000 - 301,000; Full time

Benefits offered by this job

Health insurance

Retirement benefits

Vacation leave (PTO)

Sick time

Maternity leave

Baby bonding leave

Paid holidays

Job summary

Google DeepMind’s Gemini Apps Data Engineering team seeks a senior data engineer to scale data pipelines and lead a small team of engineers. You will architect batch and real-time pipelines powering analytics and ML/AI training at scale, ensuring data quality and observability across critical datasets.

You will collaborate with Data Science, model release, model quality, and feature teams, as well as other DeepMind groups, to deliver robust data products and infrastructure in a high-growth

Qualifications

• Bachelor's degree in Computer Science or related field, or equivalent practical experience.
• 8 years of experience in software development.
• Experience with distributed data processing frameworks and workflow orchestration tools.
• Experience with Go and/or C++.
• Experience in a Technical Lead or similar role, leading a small team.

Responsibilities

• Learn more about benefits at Google.
• Architect and build scalable batch and real-time pipelines that power experimentation, product analytics, and ML/AI training loops.
• Own data quality, reliability, and observability end-to-end, including defining SLAs/SLOs for critical production datasets.
• Mentor and grow other engineers, raising the technical bar through reviews and feedback.
• Drive cross-functional engineering initiatives across multiple teams.

Skills

Go/C++

Technical leadership

Data pipelines

Go

C++

Education

Bachelor's degree in Computer Science or related field

Tools

Apache Spark

Flink

Beam

Airflow

BigQuery

Snowflake

Job description

Google DeepMind’s Gemini Apps Data Engineering team seeks a senior data engineer to scale data pipelines and lead a small team of engineers. You will architect batch and real-time pipelines powering analytics and ML/AI training at scale, ensuring data quality and observability across critical datasets.

You will collaborate with Data Science, model release, model quality, and feature teams, as well as other DeepMind groups, to deliver robust data products and infrastructure in a high-growth