Analytics Engineer, GFCO Analytics

About the Role

Coinbase is a remote-first company, but not remote-only, with quarterly in-person working sessions called 'surges.' This unique setup allows for both flexibility and collaboration, making it an ideal environment for professionals who value autonomy and teamwork. The company's intense and dynamic environment is perfect for those who are driven, motivated, and eager to push past their perceived limits.

What You Will Do

• Own the design, build, and maintenance of data models and pipelines that support CX operations, compliance reporting, and customer insights, ensuring data is accurate, timely, and well-documented.
• Partner with CX Operations, Compliance, and Product teams to translate business needs into data requirements and deliver self-serve analytics solutions that reduce manual effort.
• Build and maintain dashboards, metrics, and reporting tools that give CX leaders visibility into performance, customer trends, and compliance health.
• Drive data quality and governance within the CX data domain by implementing testing, monitoring, and documentation standards that ensure stakeholder trust in the data.
• Identify opportunities to automate recurring data workflows and reporting processes, shifting the team from reactive requests toward scalable, self-serve solutions.
• Collaborate with broader Data Engineering and Analytics teams to align on best practices, share learnings, and contribute to Coinbase's overall data infrastructure.
• Develop and maintain data models that support customer experience and compliance operations, ensuring data is accurate, complete, and accessible.
• Work closely with stakeholders to understand business needs and develop data solutions that meet those needs.
• Stay up-to-date with industry trends and emerging technologies, applying that knowledge to improve Coinbase's analytics capabilities.

What We Are Looking For

• 3+ years of experience in analytics engineering, data engineering, or a related data role, with hands-on experience building and maintaining data pipelines and models.
• Proficiency in SQL and experience with modern data stack tools such as dbt, Airflow, and cloud data warehouses (Snowflake, Databricks, or similar).
• Experience with data modeling concepts (dimensional modeling, star/snowflake schemas) and building trusted, well-documented data products.
• Familiarity with BI/visualization tools (Looker, Tableau, or similar) and experience building dashboards and self-serve analytics solutions.
• Track record of partnering with non-technical stakeholders to translate business needs into data solutions, particularly in customer experience, operations, or compliance domains.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
• Strong understanding of data governance and quality standards, with experience implementing testing, monitoring, and documentation standards.
• Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.

Nice to Have

• Experience with machine learning or statistical modeling, with a focus on applying these techniques to real-world problems.
• Familiarity with cloud-based data platforms (AWS, GCP, Azure) and experience with containerization (Docker) and orchestration (Kubernetes).
• Knowledge of data security and compliance standards, with experience implementing data encryption, access controls, and auditing mechanisms.
• Experience with agile development methodologies and version control systems (Git).

Benefits and Perks

• Competitive salary and equity package, with a focus on recognizing and rewarding individual contributions.
• Comprehensive health, dental, and vision insurance, with a generous employer match.
• 401(k) plan with a generous employer match, helping you plan for your future.
• Flexible PTO policy, allowing you to take the time you need to recharge and pursue your passions.
• Remote work stipend, providing you with the resources you need to create a productive and comfortable workspace.
• Quarterly in-person working sessions ('surges'), providing opportunities for collaboration, networking, and team-building.
• Access to cutting-edge technologies and tools, with a focus on continuous learning and professional development.
• Opportunity to work with a talented and motivated team, with a shared passion for innovation and excellence.

• When applying, be sure to highlight your experience with data modeling, pipeline development, and compliance reporting, as these are key skills for this role.
• Be prepared to discuss your approach to data governance and quality, including how you ensure stakeholder trust in the data.
• Showcase your ability to communicate complex technical concepts to non-technical stakeholders, as this is critical for success in this position.
• Consider creating a portfolio that demonstrates your skills in data engineering, analytics, and visualization, as this can help you stand out from other applicants.
• Don't be afraid to ask questions during the interview process, such as what a typical day looks like in this role or how the team approaches data-driven decision making.
• Be prepared to discuss your experience with cloud-based data platforms, machine learning, and statistical modeling, as these are valuable skills in this field.