Senior Analytics Engineer

Details

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 work culture is intense and isn’t for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there’s no better place to be.

The Analytics Engineering team bridges the gap between data engineering, data science, and business analytics by building scalable, impactful data solutions. We transform raw data into actionable insights through robust pipelines, well-designed data models, and tools that empower stakeholders across the organization to make data-driven decisions.

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.

Responsibilities

• 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.

Requirements

• 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.
• 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 scalable frameworks.
• Collaboration and Communication: Strong ability to translate technical concepts into business value for cross-functional stakeholders.
• Data Pipeline Development: Experience building, maintaining, and optimizing ETL/ELT pipelines using tools like dbt, Airflow.
• Data Visualization: Proficiency with Looker, Tableau, Superset, or Python visualization libraries.
• Development Tools: Familiarity with version control (GitHub), CI/CD, modern workflows.
• Data Architecture: Knowledge of modern data lakes/warehouses (Snowflake, Databricks) and transformation frameworks.
• Business Acumen: Ability to address business challenges through analytics engineering.
• Data savvy: Familiarity with statistics and probability.
• Bonus Skills: Experience with AWS, GCP, Docker, Kubernetes.

Benefits

• Extended Health Care Benefit - coordinates with Provincial Coverage
• Dental Care
• Vision Care
• Virtual Health Care (Consult+)
• Life & Accident Insurance
• Disability Coverage
• Employee Stock Purchase Plan (ESPP)
• Wellness Stipend
• Mobile/Internet Reimbursement
• Connections Stipend
• Learning and Development Allowance
• Employee Assistance Program
• Travel Medical Policy for Global Travelers
• Fertility Benefits
• Generous Time off/Leave Policy