Job Description:
We are seeking a Market Data Developer to design and implement solutions for sourcing, storing, and delivering end-of-day (EOD) market data used in pricing and risk calculations. This role requires strong technical skills in Python, SQL, Snowflake, AWS, and deep domain knowledge of market data across multiple asset classes. The candidate will work closely with the Risk Orchestration team to provide accurate and timely market data inputs for pricing engines and risk models.
Primary Responsibilities:
- Data Sourcing & Integration
- Source EOD market data by region from various front-office marking systems and external providers.
- Validate and normalize data across asset classes for pricing and risk consumption.
- Data Modeling & Storage
- Design and implement data models in Snowflake to persist: End-of-day prices, Volatility surfaces, Credit spread curves, Discount curves and other risk-related market data
- Infrastructure Development
- Provide solutions to pricing engines to deliver market data by region with high reliability and performance.
- Build scalable, cost-efficient Snowflake infrastructure and optimize queries for performance.
- Implement data quality checks and ensure auditability.
- Integrate with AWS SQS messaging for data readiness events.
- Collaboration
- Work closely with Market Data and Risk teams to define canonical market observables and maintain data lineage.
- Work closely with Risk Orchestration team to ensure all market data inputs meet requirements for pricing and risk analytics.
Essential Experience/ Skills:
- 7+ years of hands-on experience in developing applications using Relational Databases and Big-data platforms.
- Technical
- Strong Python (pandas, numpy, data engineering best practices).
- Advanced SQL and Snowflake (schema design, warehouse management, streams/tasks, query optimization).
- ETL/ELT pipeline development
- Domain Knowledge
- Market data concepts across multiple asset classes (Rates, FX, Credit, Equities, Commodities).
- Understanding of EOD pricing and risk inputs for VaR, sensitivities, and stress testing.
- 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
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About UsJefferies is a leading global, full-service investment banking and capital markets firm that provides advisory, sales and trading, research, and wealth and asset management services. With more than 40 offices around the world, we offer insights and expertise to investors, companies, and governments.
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, and takes affirmative action to ensure that 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 applicable 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 disabilities, as required by applicable law.
