TL;DR

Data Engineer (AI): Building robust data foundations and scalable pipelines to guide strategic decision-making in compute and product domains with an accent on complex data modeling and infrastructure optimization. Focus on designing end-to-end analytical solutions, managing high-volume metadata, and partnering with stakeholders to translate business needs into technical requirements.

Location: Must be based in Mountain View, California, US

Salary: $147,000–$211,000

Company

Google DeepMind is a world-leading research organization dedicated to advancing artificial intelligence for widespread public benefit and scientific discovery.

What you will do

  • Design, build, and optimize complex data models in SQL to address strategic business problems.
  • Develop and maintain scalable productionized data pipelines using tools like DBT and Airflow.
  • Conduct rigorous end-to-end analyses to uncover trends and model infrastructure efficiency.
  • Collaborate with engineering and product teams to identify data gaps and define architectural approaches.
  • Communicate complex analytical findings and actionable recommendations to senior leadership.
  • Leverage AI tools to accelerate analytical processes and contribute to the team's roadmap.

Requirements

  • 4+ years of professional experience in data engineering, analytics engineering, or data science.
  • Advanced proficiency in SQL, with experience in designing and optimizing complex data transformations.
  • Proficiency in Python and its data ecosystem, including Pandas, NumPy, and Scikit-learn.
  • Experience building scalable data ingestion and processing pipelines.
  • Strong communication skills to explain technical concepts to both technical and non-technical stakeholders.
  • Proven ability to translate ambiguous business challenges into structured, data-driven solutions.

Culture & Benefits

  • Direct impact on strategic AI compute and product investments.
  • Exposure to senior leadership and key organizational decision-makers.
  • Opportunity to work within a highly skilled, collaborative data and analytics team.
  • Focus on professional development and gaining expertise in AI infrastructure domains.
  • Comprehensive compensation package including bonus, equity, and benefits.