Be an integral part of a technology team that's 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 Systematic Equities Trading Business. The role would sit in the Equities Trading Data & Analytics technology team. As a Vice President Software Engineer at JPMorgan Chase within the agile technology team, 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, and your profound technical expertise and problem-solving methodologies will be utilized to address a wide range of challenges across various technologies and applications.
Job Responsibilities
- Build and support fast, reliable, globally consistent data pipelines (data ingestion, cleaning, backfilling, storing) for the research and execution systems ensuring data integrity and low-latency access for research and trading.
- Work with the research and trading teams to onboard new datasets efficiently and consistently for use globally by the business.
- Design and build robust tools and frameworks to support quantitative research and production trading.
- Design, build and support research infrastructure (e.g. data access APIs, high performant and scalable simulation environments, feature and strategy signal stores)
- Build and support research and trading analytics libraries (e.g. markouts, strategy analytics)
- Serve as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influence peers and project decision-makers to consider the use and application of leading-edge technologies
Required Qualifications, Capabilities, And Skills
- 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. Comfortable with scientific & dataset libraries such as pandas, 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 tackle design and functionality problems independently 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 experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Knowledge of machine learning, statistical techniques and related libraries.
Preferred Qualifications, Skills And Capabilities
- Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets
- Additional knowledge of Java / C++ is a strong plus.
- Practical cloud native experience is a plus.
- Practical cloud experience is a plus.