Analytics Engineer

About the position

We're looking for an experienced analytics engineer to join Google DeepMind's internal data & analytics group. Working at the intersection of insights and engineering, you'll use your expertise to build data pipelines to generate actionable insights around the investment and impact of our research portfolio, contributing directly to DeepMind's mission of bringing the benefits of AI to the world! You'll join the Core Analytics Team (CAT) within the Tech Ops & Analytics group at Google DeepMind, comprising a software engineer, analytics engineers & data scientists. We ultimately aim to drive better organisational decisions - blending our technical skillset with rich stakeholder relationships to deliver impact. The outcomes of our work, ranging across topics like (but not limited to!) compute purchase and efficiency, research organisation, and recruitment optimisation, directly influence Google DeepMind's progress towards our mission.

Responsibilities

• Build ETL pipelines to convert raw data into actionable insights for stakeholders.
• Shape and ensure compliance with internal data governance policies.
• Work with partners to identify relevant high-level product & business questions and propose relevant data-driven analysis.
• Write queries and conduct rigorous, verifiable analysis (SQL, Python) to answer those questions.
• Develop tools (dashboards, reports, web apps) to enable continuous monitoring of key metrics and enable user self-service.
• Communicate via presentations and written reports to a wide variety of stakeholders (with varying levels of seniority, technical and domain familiarity) - following through to ensure impact.
• Manage several projects simultaneously, exhibiting good project management skills (timelines, expectations, progress, etc.).
• Collaborate effectively as part of a team of other data analysts, engineers and project managers.
• Recommend changes to product/engineering roadmaps to improve data quality in source systems.
• Submit tested code into source control for review.
• Coach and mentor others in their own use of analytical tools and techniques.

Requirements

• Advanced SQL & Data Expertise: You possess advanced SQL skills and are experienced in designing, building, and optimizing data models.
• Strong understanding of data warehousing principles and are proficient in using SQL to perform analysis and validate your data pipelines.
• Strong track record of collaborating with stakeholders to understand their data needs, translate complex business problems into well-defined technical requirements and communicate technical solutions.
• Comfortable working in a dynamic environment and consistently meet deadlines while maintaining a high standard of work.
• Self-starter who can take ownership of projects, independently mastering new technologies to implement solutions to complex data engineering and analysis challenges.

Nice-to-haves

• Experience with publication analytics or impact tracking.
• Proficiency in Python and the PyData stack (e.g., Pandas, Scikit-learn, NumPy, Jupyter).
• A solid understanding of statistical concepts and the ability to apply them in analysis.
• A passion for continuous learning and expanding your skill set.
• The ability to translate data into meaningful stories and present actionable insights to senior stakeholders.
• A collaborative mindset and eagerness to work with others to achieve common goals.

Benefits

• Base salary range between $122,000 - $186,000,000 + bonus + equity + benefits.