Used Tools & Technologies
GenAIRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 6
SQL @ 6
dbt @ 6
Databricks @ 6
Reporting @ 3
Snowflake @ 6
Compliance @ 3
Generative AI @ 3
AI @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
At Coinbase you will build and maintain production-grade data foundations that regulatory obligations depend on. The Compliance Data team owns the Compliance Data Mart (CDM), Coinbase's canonical source of truth for user, transaction, and compliance data. You will own the full lifecycle of data models and pipelines that downstream reporting, analytics, and AI workflows build on, and deliver accurate, timely data for regulatory needs. Coinbase is a remote-first company; expect quarterly in-person working sessions called “surges.”
Responsibilities
- Own end-to-end development of production-grade data models and pipelines for the CDM, covering user, transaction, and compliance data across retail and institutional product lines, from architecture through deployment and maintenance.
- Build data quality checks, data contracts, validation logic, and monitoring to protect data integrity before issues propagate to downstream reports or workflows.
- Partner with upstream engineering teams to fix data gaps and absorb product changes at the source; take accountability for data issues across the stack.
- Support live regulatory exams, audits, and ad hoc regulator requests with accurate, timely data, balancing reactive time-sensitive work with long-term foundational projects.
- Automate recurring manual workflows into scalable pipelines and self-serve tooling, enabling downstream teams and AI agents to answer their own questions.
Requirements
- 2+ years of experience building and maintaining production data pipelines and data models.
- Strong proficiency in SQL, Python, dbt, and a modern data warehouse platform (examples: Snowflake, Databricks).
- Track record implementing data quality frameworks including data contracts, validation logic, reconciliation, and monitoring.
- Experience supporting time-sensitive, high-stakes data needs (regulatory exams, audits, or financial reporting) where accuracy and timeliness are critical.
- Demonstrated ability to turn tribal knowledge and recurring manual workflows into durable, documented infrastructure.
- Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable workflow improvements.
Benefits
- Annual base salary range (excluding equity and bonus): $152,405 — $179,300 USD.
- Total compensation may also include equity, bonus eligibility, and benefits (medical, dental, vision, 401(k)).
Other details
- Job ID: P77413
- Remote location: United States (remote-first, with quarterly in-person surges)