Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Be an integral part of a technology team that is constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Python Quant Data Engineer, you will help build the technology for the Systematic Equities Trading Business within the Equities Trading Data & Analytics technology team. In the role of Vice President Software Engineer at JPMorgan Chase, you will play a crucial role in improving, developing, and delivering top-tier technology products in a secure, stable, and scalable manner. Your skills and contributions will have a substantial impact on the business, leveraging your profound technical expertise and problem-solving methodologies to address a wide range of challenges across various technologies and applications.

Key responsibilities include building and supporting fast, reliable, globally consistent data pipelines (data ingestion, cleaning, backfilling, storing) for research and execution systems ensuring data integrity and low-latency access for research and trading. You will collaborate with research and trading teams to onboard new datasets efficiently and consistently for global business use. Additionally, you will design and build robust tools and frameworks to support quantitative research and production trading, as well as research infrastructure such as data access APIs, high-performance scalable simulation environments, and feature and strategy signal stores. You will also build and support research and trading analytics libraries and serve as a subject matter expert in one or more focus areas. Active contribution to the engineering community by advocating firmwide frameworks, tools, and software development life cycle practices is expected, along with influencing peers and project decision-makers to consider leading-edge technologies.

Experience
- Design and implementation of front-office systems for quant trading
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Strong expertise in Python and familiarity with scientific and dataset libraries such as pandas and numpy
- Experience with KDB/Q
- Knowledge of data pipelines, market data processing, and backtesting workflows
- Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines
- Ability to independently tackle design and functionality problems with little to no oversight
- Proficiency in automation and continuous delivery methods
- In-depth knowledge of the financial services industry and their IT systems
- Academic background in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Knowledge of machine learning, statistical techniques, and related libraries

About you
Self-motivated and proactive with strong problem-solving skills. Able to work effectively in an agile team environment and communicate complex technical concepts clearly. Passionate about technology innovation and continuous improvement. Committed to diversity and inclusion and able to contribute positively to a collaborative workplace culture.

Qualifications
- Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets is an asset
- Additional knowledge of Java and/or C++ is a strong plus
- Practical cloud native and cloud experience is a plus