We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Bank's Equities Technology - Prime Services team, youare an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Design and Implement data pipelines and data stores that will be leveraged by quant models
- Work closely with Trading Desk, Production Support, Quantitative Researchers and other Global Technology teams on Data Products and Analytics
- Execute software solutions, design, develop, and technically troubleshoot with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems
- Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture
- Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Add to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years of applied experience
- Advanced proficiency in Python for data engineering
- Demonstrated ownership of data quality/observability, Lineage and Governance in production environments
- Strong knowledge of SQL and schema design for analytical and time series workloads performance tuning on columnar data
- Expertise in data management on AWS (S3, Glue, Athena, MWAA)
- Hands-on practical experience delivering system design, application development, testing and mission critical operational data flows
- Practical cloud native experience
Preferred qualifications, capabilities, and skills
- Prior knowledge of Capital Markets will be a strong plus
- Data streaming knowledge on frameworks like Kafka, AMPS will be beneficial
- Familiarity and prior experience on KDB/q will be beneficial
- Experience of working with and manipulating datasets using Pandas/Numpy/Scikit will be desirable
