Staff Software Engineer, Gemini App, Data Engineering, Deepmind

Google Google · Big Tech · Mountain View, CA +3

Staff Software Engineer on the Gemini Apps Data Engineering team at Google DeepMind. This role focuses on architecting and operating data pipelines for telemetry, analytics, and ML/AI training data at a massive global scale. The engineer will provide technical leadership, scale infrastructure, build durable data products, and drive cross-functional initiatives to support Gemini's growth and model improvement. The role involves working with Data Science, model release, and feature teams, and mentoring junior engineers.

What you'd actually do

  1. Work closely with our Data Science counterparts in definition and driving the goals for a Modern Data Warehouse.
  2. Architect and build scalable batch and real-time pipelines that power experimentation, product analytics, and ML/AI training loops.
  3. Own data quality, reliability, and observability end-to-end, including defining and operating Service Level Agreements (SLAs)/ Service Level Objectives (SLOs) for critical production datasets.
  4. Mentor and grow other engineers, raising the technical bar through design reviews, code reviews, and actionable feedback.
  5. Drive cross-functional engineering initiatives that span multiple teams, translating ambiguous requirements into technical designs.

Skills

Required

  • Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
  • 8 years of experience in software development.

Nice to have

  • Experience with Apache Spark, Flink, Beam, Airflow, or BigQuery/Snowflake or other similar infrastructure.
  • Experience developing, debugging, and supporting large-scale data pipelines.
  • Experience with distributed data processing frameworks and workflow orchestration tools.
  • Experience in Go/C++.
  • Experience in a technical Lead or similar role, ideally setting technical direction for a small group of executive and junior software engineer.
  • Ability to address daily business data requirements, ensure that development obstacles are cleared to maintain the Gemini App's changing growth.

What the JD emphasized

  • scale our infrastructure
  • durable data products
  • critical engineering initiatives
  • massive global scale
  • scale the data pipelines
  • power model and product improvement
  • accelerate high-quality product innovation
  • billions of users
  • pushing the boundaries
  • exceptional results
  • power experimentation, product analytics, and ML/AI training loops
  • data quality, reliability, and observability end-to-end
  • defining and operating Service Level Agreements (SLAs)/ Service Level Objectives (SLOs)
  • technical Lead

Other signals

  • Gemini Apps
  • massive growth
  • scale our infrastructure
  • durable data products
  • critical engineering initiatives
  • massive global scale
  • scale the data pipelines
  • power model and product improvement
  • Google DeepMind
  • accelerate high-quality product innovation
  • billions of users
  • pushing the boundaries
  • exceptional results
  • power experimentation, product analytics, and ML/AI training loops
  • data quality, reliability, and observability end-to-end
  • defining and operating Service Level Agreements (SLAs)/ Service Level Objectives (SLOs)
  • technical Lead