Staff Analytics Engineer

Analytics Engineer

Ready to be pushed beyond what you think you're capable of? At Coinbase, our mission is to increase economic freedom in the world. It's a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system. To achieve our mission, we're seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up. We want someone who will run towards, not away from, solving the company's hardest problems.

Our team combines technical expertise with a deep understanding of the business to unlock the full potential of our data. We prioritize data quality, reliability, and usability, ensuring stakeholders can rely on our data to drive meaningful outcomes.

What We Do:

• Trusted Data Sources: Develop and maintain foundational data models that serve as the single source of truth for analytics across the organization.
• Actionable Insights: Empower stakeholders by translating business requirements into scalable data models, dashboards, and tools.
• Cross-Functional Collaboration: Partner with engineering, data science, product, and business teams to ensure alignment on priorities and data solutions.
• Scalable Data Products: Build frameworks, tools, and workflows that maximize efficiency for data users, while maintaining high standards of data quality and performance.
• Outcome-Focused Solutions: Use modern development and analytics tools to deliver value quickly, while ensuring long-term maintainability.

What You'll Be Doing:

Analytics engineer is a hybrid Data Engineer/Data Scientist/Business Analyst role that has the expertise to understand data flows end to end, and the engineering toolkit to extract the most value out of it indirectly (building tables) or directly (solving problems, delivering insights).

Expectations:

• Be the expert: Quickly build subject matter expertise in a specific business area and data domain. Understand the data flows from creation, ingestion, transformation, and delivery.
• Generate business value: Interface with stakeholders on data and product teams to deliver the most commercial value from data (directly or indirectly).
• Focus on outcomes not tools: Use a variety of frameworks and paradigms to identify the best-fit tools to deliver value.

What We Look For In You:

• Customer Support Data Experience: Familiarity with data elements and processes supporting successful Customer Support initiatives, including employee performance monitoring, workforce/staffing inputs, and the handling of sensitive PII across a broad stakeholder base.
• Data Modeling Expertise: Strong understanding of best practices for designing modular and reusable data models (e.g., star schemas, snowflake schemas).
• Prompt Design and Engineering: Expertise in prompt engineering and design for LLMs (e.g., GPT), including creating, refining, and optimizing prompts to improve response accuracy, relevance, and performance for internal tools and use cases.
• Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization.
• Intermediate to Advanced Python: Expertise in scripting and automation, with experience in Object-Oriented Programming (OOP) and building scalable frameworks.
• Collaboration and Communication: Strong ability to translate technical concepts into business value for cross-functional stakeholders. Proven ability to manage projects and communicate effectively across teams.
• Data Pipeline Development: Experience building, maintaining, and optimizing ETL/ELT pipelines, using modern tools like dbt, Airflow, or similar.
• Data Visualization: Proficiency in building polished dashboards using tools like Looker, Tableau, Superset, or Python visualization libraries (Matplotlib, Plotly).
• Development Tools: Familiarity with version control (GitHub), CI/CD, and modern development workflows.
• Data Architecture: Knowledge of modern data lake/warehouse architectures (e.g., Snowflake, Databricks) and transformation frameworks.
• Business Acumen: Ability to understand and address business challenges through analytics engineering.
• Data Savvy: Familiarity with statistics and probability.
• Bonus Skills: Experience with cloud platforms (e.g., AWS, GCP). Familiarity with Docker or Kubernetes.

Pay Transparency Notice: Depending on your work location, the target annual salary for this position can range as detailed below. Full time offers from Coinbase also include target bonus + benefits (including medical, dental, vision and 401(k)). Pay Range: $207,000—$244,100 USD