Senior Market Risk Developer – Historical Timeseries

Position / Group description:

The Risk Technology group builds and supports a global risk platform enabling the Risk Management group to oversee all areas of risk across the Firm. The risk platform provides capabilities for measuring, quantifying, analyzing, reporting, and controlling exposures across market and credit.

The position is for a Techno-Functional Developer to design, enhance, and maintain the Market Risk Time Series infrastructure built on Snowflake and AWS. This role requires strong technical skills combined with deep domain expertise in market risk, including VaR , end-of-day market data , and historical time series. The candidate will work closely with the Market Data team and Risk stakeholders to ensure accurate, scalable, and auditable data solutions for risk analytics.

Primary Responsibilities:

• Data Sourcing & Integration
• Source historical market data from multiple internal and external providers.
• Integrate with quant libraries to identify data quality issues and validate risk inputs.

Data Quality & Remediation

• Integrate with Quant APIs to detect and remediate common data quality issues (gaps, stale data, outliers, misalignments).
• Implement algorithms for gap-filling, back-filling, and anomaly correction to ensure data is fit for VaR and SVaR calculations.

Infrastructure Development

• Build and enhance Snowflake-based time series infrastructure for scalability and performance.
• Develop Python ETL/ELT pipelines and optimized SQL models for historical time series storage and retrieval.

Collaboration & Governance

• Work closely with Market Data and Risk teams to define canonical market observables and maintain data lineage.
• Ensure reproducibility and auditability of risk inputs for regulatory compliance.

Essential Experience/ Skills:

• 7+ years of hands-on experience in developing applications using Relational Databases and Big-data platforms.
• Strong Python (pandas, numpy, data engineering best practices).
• Advanced SQL and Snowflake (warehouse management, streams/tasks, query optimization).

Domain Knowledge

• Market risk concepts: VaR, SVaR, sensitivities, stress testing.
• Handling end-of-day market data and historical time series across asset classes.
• Techno-Functional
• Ability to translate risk requirements into technical solutions and data contracts.
• Bachelor’s degree, preferably in Computer Science, Engineering, Mathematics, or similar technical discipline

Personal Attributes:

• Strong analytical and problem-solving skills, including the ability to troubleshoot and resolve complex data related issues
• Strong verbal and written communication skills
• Self-starter and entrepreneurial in approach
• Ability to escalate and follow-up proactively
• Good time management skills

At Jefferies, we believe that diversity fosters creativity, innovation and thought leadership through the infusion of new ideas and perspectives. We have made a commitment to building a culture that provides opportunities for all employees regardless of our differences and supports a workforce that is reflective of the communities where we work and live. As a result, we are able to pool our collective insights and intelligence to provide fresh and innovative thinking for our clients.

Jefferies is an equal employment opportunity employer. We practice equal opportunity for all, and all qualified applicants will receive consideration for employment without regard to race, creed, color, national origin, ancestry, religion, gender, pregnancy, age, physical or mental disability, marital status, sexual orientation, gender identity or expression, veteran or military status, genetic information, reproductive health decisions, or any other factor protected by law. We are committed to hiring the most qualified applicants and complying with all federal, state, and local equal employment opportunity laws. As part of this commitment, Jefferies will extend reasonable accommodations to individuals with qualified disabilities, as appropriate, under applicable law.