Staff Software Engineer, Gemini App, Data Engineering, DeepMind at DeepMind

Job description

The Gemini Apps Data Engineering team architects and operates the data pipelines that deliver critical telemetry across all Gemini surfaces. We combine deep technical expertise with Google-scale operating experience to solve the unique data issues inherent in building a transformative, global product during a time of massive growth! Gemini’s user base is growing continuously and our traffic has sometimes even doubled just over the course of a week. In this role, you will provide the technical leadership necessary to scale our infrastructure. You will architect durable data products and drive critical engineering initiatives across multiple teams to ensure we continue delivering metrics and training data quickly, reliably, and accurately at a massive global scale. Leveraging your experience in building and running scalable systems, and utilizing modern data warehouse infrastructure at Google, you will lead a small team of executive and junior engineers to scale the data pipelines that drive Gemini Apps’s analytics and power model and product improvement. You will work directly with key stakeholders, including our Data Science, model release, model quality, and feature teams, as well as teams across DeepMind, to identify and solve key problems to help make Gemini the next billion-user product. Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google . • Work closely with our Data Science counterparts in definition and driving 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)/ Service Level Objectives (SLOs) for critical production datasets. • Mentor and grow other engineers, raising the technical bar through design reviews, code reviews, and actionable feedback. • Drive cross-functional engineering initiatives that span multiple teams, translating ambiguous requirements into technical designs. • Bachelor's degree in Computer Science or related technical field, or equivalent practical experience. • 8 years of experience in software development. Minimum qualifications: • Bachelor's degree in Computer Science or related technical field, or equivalent practical experience. • 8 years of experience in software development. Preferred qualifications: • 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.

Requirements

Must-haves

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Work closely with our Data Science counterparts in definition and driving 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)/ Service Level Objectives (SLOs) for critical production datasets.
Mentor and grow other engineers, raising the technical bar through design reviews, code reviews, and actionable feedback.
Drive cross-functional engineering initiatives that span multiple teams, translating ambiguous requirements into technical designs.
Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
8 years of experience in software development.
Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
8 years of experience in software development.

Nice-to-haves

US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlgo

Platform: google
Effort: medium