Senior Data Engineer
Senior Data Engineer building ETL pipelines, data processing systems, and Lakehouse architecture on AWS to map decision-maker networks. Requires 6+ years experience, expert SQL, Spark, and data warehousing tools.
Member of Global Risk Management, Quantitative Financial Risk
Develops quantitative tools and scalable Python pipelines for credit, market, and liquidity risk analysis at a digital asset firm. Requires 8+ years in quantitative finance, advanced degree, and expertise in stress testing and real-time risk monitoring.
United StatesData EngineeringRemote8+ YOE
About the role
Responsibilities
- Design, build, and maintain quantitative analysis tools for credit, market, and liquidity risk assessment
- Build scalable analytics pipelines in Python to automate reporting, data transformation, and real-time risk monitoring
- Execute portfolio margin stress tests and scenario analysis under tight timelines, delivering actionable insights to stakeholders
- Lead end-to-end development of quantitative analysis tools from problem definition through production deployment with minimal oversight
- Run ad-hoc real-time analysis and deliver under pressure
- Navigate ambiguous risk problems by selecting appropriate quantitative methods and articulating trade-offs to stakeholders
- Collaborate closely with Trading, Sales, Compliance, Treasury, and Operations to ensure risk analysis and tools are embedded in business decisions
- Monitor industry trends, regulatory developments, and emerging best practices in quantitative risk management
- Translate complex quantitative concepts into clear, actionable insights for technical and non-technical audiences
- Mentor junior team members on quantitative methods, analytics tooling, and professional development
Requirements
- 8+ years of experience in quantitative finance, financial risk management, or a related quantitative discipline
- Advanced degree (Master's or PhD) in a quantitative field
- Proven track record of building quantitative analysis tools for risk management (credit, market, liquidity risk)
- Deep expertise in risk monitoring and reporting, including experience building or operating real-time risk dashboards and producing executive-level risk reports
- Experience with portfolio stress testing and scenario analysis in a professional setting
- Experience working with large datasets and analytical tools to support risk analysis
- Experience with regulators and regulatory exams
Nice-to-Haves
- Experience with digital assets, crypto, or blockchain-related financial products
- Understanding of operational risk and how it intersects with credit, market, and liquidity risk
Skills
PythonQuantitative AnalysisRisk ManagementStress TestingScenario AnalysisAnalytics PipelinesReal-Time DashboardsLarge DatasetsPortfolio MarginingFinancial Modeling
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