Analytics Engineer

The Analytics Engineering team builds and maintains trusted data infrastructure across the organization. This role focuses on building reliable, well-governed data foundations for compliance and regulatory reporting across Coinbase's international entities.

As Coinbase's international presence grows, so does the volume and complexity of regulatory data requirements. Your mission is to build a platform: a reliable, automated, self-serve data foundation for regulatory reporting. You will start by developing deep expertise in the regulatory data landscape, then progressively build data models, automate recurring workflows, and enable compliance stakeholders to answer regulatory questions independently with confidence and accuracy. The goal is to transition from reactive, manual reporting toward a scalable platform that minimizes manual data pulls work over time.

We are actively evolving toward an AI-agent-driven data stack where humans write specs, AI generates data models, and agents handle analytics on clean data domains. You will be an early builder of this operating model within the regulatory reporting domain.

What We Do

• Build and maintain the Regulatory Data Mart as the single source of truth for regulatory reporting across Coinbase's international entities, handling the nuances of multi-entity, multi-jurisdiction reporting
• Enable compliance stakeholders to self-serve regulatory data needs rather than depending on ad-hoc data pulls
• Build AI-driven workflows that automate regulatory reporting while maintaining the highest accuracy standards
• Ensure Coinbase meets regulatory reporting SLAs and stays compliant across international markets
• Own end-to-end data quality through data contracts, validation checks, and monitoring

What you’ll be doing (ie. job duties): 

• Design and build data models that serve as the foundation for regulatory reporting, with the entity-level granularity and definitions regulators require
• Build and maintain data quality checks, monitoring, and data contracts; implement reconciliation against prior submissions
• Write specs and definitions that AI tools use to generate pipelines and answer regulatory questions accurately
• Standardize regulatory metric definitions, entity-specific nuances, and historical reporting decisions into durable, machine-readable formats
• Partner with Compliance, Legal, and Business Operations to translate regulatory requirements into data models, and with upstream Engineering to ensure accurate, well-contracted source data
• Shift progressively from handling regulatory data requests toward building automated, self-serve solutions that reduce manual effort over time
• Maintain clear, structured documentation of business logic optimized for AI agent consumption, so agents can reliably trace and query regulatory data end-to-end

What we look for in you (ie. job requirements)

What We Look For in You

• You think in systems, not tasks: When something is broken or a data request lands, you move toward it and ask "how do I make sure no one ever has to do this manually again?"
• You treat AI as your first collaborator: You break problems down, delegate execution to agents, and focus on what requires human judgment. You design data, metadata, and documentation so agents can reason over them without human translation. You've developed the taste to know when AI output is correct vs. just convincing
• You learn fast in unfamiliar territory: You pull knowledge from people, docs, and data quickly and turn tribal knowledge into durable infrastructure. You understand that building the right platform means doing the work manually first to learn the patterns worth automating
• You choose accuracy over speed and it shows: Regulatory data cannot be wrong. Data contracts, validation frameworks, quality checks. You know that trust is earned through rigor, especially when agents are generating the pipelines
• You're strong in the analytics engineering fundamentals: Advanced SQL, Python, data modeling (star/snowflake, OBTs, SCDs), pipeline development (dbt, Airflow), and modern warehouse architecture (Snowflake, Databricks). These aren't resume keywords; they're tools you reach for daily
• You operate independently: You proactively identify what needs to be done, and drive it forward without waiting for direction from your manager or stakeholders.