Data Engineer - Risk & Compliance

Role overview Build and operate data pipelines and models that support risk monitoring, compliance, regulatory reporting, and audit evidence. The role turns large-scale blockchain and internal data into reliable, explainable datasets, working with engineering, analytics, data science, risk, and compliance partners. You will own delivery and ongoing operation of your work, with increasing responsibility as you develop domain knowledge.

Responsibilities - Gather data needs from partner teams and translate them into clear requirements, business logic, models, and pipelines. - Develop understanding of how data supports transaction monitoring, sanctions and anti-money-laundering screening, regulatory reports, and audits. - Build, maintain, and operate data models and pipelines; add quality checks, alerts, runbooks, and on-call support. - Ingest and model blockchain data, accounting for reorganizations, late or missing records, and upstream schema changes. - Deliver new data sources, domain models, and backfills; investigate failures and discrepancies and resolve root causes. - Apply access controls and privacy requirements, review peer work, document changes, and keep partners informed of progress and risks.

Requirements - A bachelor’s degree in a quantitative or technical field, or equivalent experience. - At least three years building and operating production data pipelines and models. - Proficiency in SQL and Python, with experience using a cloud data warehouse, an orchestration tool such as Airflow, and a transformation tool such as dbt. - Ability to deliver well-scoped work independently with tested, reliable code. - Strong ownership, attention to detail, clear communication, and a collaborative approach with technical and nontechnical partners.

Nice to have - Experience with blockchain data, financial services, banking, risk, compliance, or another regulated industry.

Benefits and work setup Remote work is available. The listed base pay range is $122,500–$165,000; starting pay may vary based on location, experience, skills, and qualifications.