Title: Vice Presidents, Financial Markets - Engineering
Employer: ING Financial Services, LLC
Location: New York, NY
Salary range: $200,000 – $225,000
Job Description:
Work within the Financial Markets division of the Front Office Engineering team, delivering cutting edge technology that directly impacts ING FM’s global financial institution and corporate client base. As a senior developer, leverage deep expertise in Python to develop and scale ING’s client-facing digital capabilities, applying a high level of autonomy, vision, creativity, and determination to challenge the status quo. Work with ING’s financial markets products, including swaps and options, across multiple asset classes while utilizing strong programming, analytical, and Python coding skills to develop innovative, client-facing digital solutions and improve existing workflows through fully automated processes. Manage large-scale financial datasets, design and implement quantitative algorithms and data engineering structures, and rapidly prototype minimum viable products (MVPs) to enhance sales-trader workflows. Execute full-stack development, build user-facing features and bots, integrate REST-based APIs, and leverage cloud computing to ensure scalability and efficiency. Apply expertise in Q/SQL, Python, Git, and Azure, while integrating with external multi-dealer platforms, including Tradeweb, MarketAxess, and Bloomberg, to streamline execution and enhance trading processes.
Minimum Requirements:
Bachelor’s degree or foreign equivalent in Finance, Economics, or Software Engineering and minimum 4 years of experience as a Data Analyst or related working within a technological environment. Must have experience working with the following: financial products swaps and options across multiple asset classes including FX, fixed income, equities, commodities, interest rates, and derivatives; end-to-end application development, building user-facing features, and managing the entire technology stack, ensuring scalability, efficiency, and usability; automation and workflow optimization including developing bots and integrating REST-based APIs to enhance business processes and automate RFQ processing for trading workflows; Python, SQL, and cloud computing, enabling the development of high-performance financial applications; financial technology integration including working with FI Syndication and DCM; KDB+ and q programming, leveraging high-speed time-series databases for real-time analytics and market data processing to support front-office trading applications; and big data and low-latency computing including performing data mining, executing big data queries, and implementing low-latency programming for high-speed financial applications.
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