Staff Software Engineer, Gemini App, Data Engineering, DeepMind
About The Position
As part of the Gemini Apps Data Engineering team, the Staff Software Engineer will architect and operate data pipelines that deliver critical telemetry across Gemini surfaces. The role calls for deep technical expertise and large-scale operating experience to address data challenges in a rapidly growing global product. The engineer will provide technical leadership to scale infrastructure, architect durable data products, and drive engineering initiatives across multiple teams so that metrics and training data are delivered quickly, reliably, and accurately at global scale. The role includes using Google’s modern data warehouse infrastructure and leading a small team of engineers to scale pipelines supporting Gemini Apps analytics and model and product improvement. The engineer will work with stakeholders in Data Science, model release, model quality, and feature teams, as well as teams across DeepMind, to identify and solve problems. Google DeepMind describes itself as a pioneering AI lab whose interdisciplinary teams advance AI development for complex global challenges and product innovation, with safety and ethics as priorities.
Requirements
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
- 8 years of experience in software development.
Nice To Haves
- Experience with Apache Spark, Flink, Beam, Airflow, BigQuery, Snowflake, or similar infrastructure.
- Experience developing, debugging, and supporting large-scale data pipelines.
- Experience with distributed data processing frameworks and workflow orchestration tools.
- Experience in Go or C++.
- Experience in a technical lead or similar role, ideally setting technical direction for a small group of engineers.
- Ability to address daily business data requirements and clear development obstacles to support the Gemini App's changing growth.
Responsibilities
- Work closely with Data Science counterparts to define and drive the goals for a Modern Data Warehouse.
- 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 and operating Service Level Agreements (SLAs) and Service Level Objectives (SLOs) for critical production datasets.
- Mentor and grow other engineers through design reviews, code reviews, and actionable feedback.
- Drive cross-functional engineering initiatives spanning multiple teams and translate ambiguous requirements into technical designs.
- Provide technical leadership to scale infrastructure and architect durable data products.
- Lead a small team of engineers to scale data pipelines supporting Gemini Apps analytics and model and product improvement.
- Work with stakeholders across Data Science, model release, model quality, feature teams, and DeepMind to identify and solve problems.
Benefits
- 20% bonus target
- Equity
- Benefits (details are linked on Google's careers benefits page)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
