Data Engineer

The successful candidate will be responsible for monitoring, managing, and enhancing equity and commodity derivatives market data. This role combines financial markets expertise, data engineering, and analytical problem-solving to ensure the accuracy, integrity, and reliability of complex datasets and valuation models. The individual will work closely with Sales, Product Specialists, Account Management and Market Data colleagues across global regions to ensure responsive, high-quality service to existing and prospective clients.

Responsibilities

Identify data anomalies and implement appropriate remediation actions to improve data quality, consistency, and reliability.
Calibrate, maintain, and enhance model parameters to sustain high-quality data outputs.
Design, develop, and implement automated monitoring and alerting solutions to preserve data integrity and operational efficiency.
Apply programming skills and financial markets experience to clean and manage large volume of historical and real-time implied market data.
Perform in-depth analysis of derivatives markets and leverage quantitative and technical expertise to support complex structured product pricing and portfolio valuation inquiries.
Collaborate with internal stakeholders to investigate client issues, deliver timely resolutions, and improve product quality.
Stay informed of industry developments, market trends, and emerging technologies across equity and commodity derivatives markets.
Communicate clearly in both writing and verbally: escalate issues and client requirements to Quants, and translate technical processes and solutions for Business Partners and Sales stakeholders.

Knowledge And Experience

Bachelor's or Master’s degree required, preferably in Financial Engineering, Mathematics, Statistics, Computer Science, or a related quantitative discipline.
3+ years of working with financial market data and data management. Experience with equity and commodity derivatives is a plus.
Experience working with data products, valuation services, and financial data platforms.
Strong analytical, quantitative, and problem-solving skills with the ability to investigate and resolve complex data issues.
Advanced proficiency in SQL and Python preferred.
Experience with artificial intelligence and machine learning is a plus.
Ability to multitask, prioritize, and work with tight deadlines.
Ability to collaborate with internal teams to facilitate data management processes and solutions.
Strong organizational skills with acute attention to details.