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, you are 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 modelsWork closely with Trading Desk, Production Support, Quantitative Researchers and other Global Technology teams on Data Products and AnalyticsExecute software solutions, design, develop, and technically troubleshoot with ability to think beyond routine or conventional approaches to build solutions or break down technical problemsCreate secure and high-quality production code and maintain algorithms that run synchronously with appropriate systemsProduce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code developmentGather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systemsProactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architectureLead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologiesAdd 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 experienceAdvanced proficiency in Python for data engineeringDemonstrated ownership of data quality/observability, Lineage and Governance in production environmentsStrong knowledge of SQL and schema design for analytical and time series workloads; performance tuning on columnar dataExpertise in data management on AWS (S3, Glue, Athena, MWAA)Hands-on practical experience delivering system design, application development, testing and mission critical operational data flowsPractical cloud native experiencePreferred qualifications, capabilities, and skillsPrior knowledge of Capital Markets will be a strong plusData streaming knowledge on frameworks like Kafka, AMPS will be beneficialFamiliarity and prior experience on KDB/q will be beneficialExperience of working with and manipulating datasets using Pandas/Numpy/Scikit will be desirable