Analytics Engineer

About the role

As an Analytics Engineer at Coinbase, you will design and build data models essential for regulatory reporting. Your work will ensure that data meets the granularity and definitions required by regulators, which is critical for compliance.

You will collaborate with teams across Compliance, Legal, and Business Operations to translate regulatory requirements into effective data models. Success in this role involves not only maintaining data quality but also developing automated solutions to streamline data requests over time.

The salary for this position ranges from $82,000 to $138,000, reflecting the importance of accurate regulatory data.

Skills that matter here

• SQL: You will use SQL to design and build data models for regulatory reporting.
• Python: Python will be essential for developing data processing pipelines and automation.
• data modeling: Data modeling skills are critical for creating accurate and compliant data structures.
• dbt: You will leverage dbt for building and managing data transformation workflows.
• Airflow: Airflow will be used to orchestrate and schedule your data pipelines.
• Snowflake: Experience with Snowflake will be necessary for modern data warehouse architecture.

Who this role suits

• You are a systems thinker who seeks to prevent repetitive issues.
• You embrace AI as a collaborator and delegate tasks effectively.
• You can quickly learn and adapt in new areas, transforming knowledge into infrastructure.
• You prioritize accuracy and have a strong foundation in analytics engineering.

From the employer

What you’ll be doing:

• 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:

• 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 learn fast in unfamiliar territory: You pull knowledge from people, docs, and data quickly and turn tribal knowledge into durable infrastructure.
• You choose accuracy over speed and it shows: Regulatory data cannot be wrong.
• 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).
• You operate independently: You proactively identify what needs to be done, and drive it forward without waiting for direction from your manager or stakeholders.

Pay Transparency Notice:

• The target annual base salary for this position can range as detailed below. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, and vision).
• Annual base salary range (excluding equity and bonus): £100,620 — £111,800 GBP.