Bring your Data Engineering skills to the next level and join the AIML Data Platforms Fusion Data Management Team. In this role as a Lead Analytics Data Engineer you will bring your experience with Python / Java / Spark knowledge to help the Securities Services business identify opportunities to improve efficiency, increase revenue, optimize the operating model and risk framework and create value added data driven Products for our Clients. As a Lead Data Engineer at JPMorgan Chase on the Corporate AIML Data Platforms Fusion Data Management Team, you play a key role in an agile team, designing and delivering secure, stable, and scalable technology products. You are responsible for implementing critical technology solutions across various technical areas to support the firm's business goals. You collaborate with teams, including Product Development and Business users, to develop applications on our AWS Analytics platform. Your role involves hands-on design and development of applications, formulating analytics strategies, and ensuring data and logic consistency and optimization across applications. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development. Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture. Contributes to software engineering communities of practice and events that explore new and emerging technologies. Adds to team culture of diversity, equity, inclusion, and respect. Required qualifications, capabilities, and skills Formal training or certification on Software Engineering concepts and 5+ years applied experience. Excellent Python knowledge with experience with Web application frameworks such as Fast API Experience in building data pipelines using Python / Java / Pyspark Working knowledge in Python base rest API builds including Fast API Experience pipeline orchestration tools Argo, Airflow etc. Strong database skills with a thorough understanding of databases and data modelling concepts. Solid understanding in Object oriented programming concepts and Design patterns. Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages. Overall knowledge of the Software Development Life Cycle Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security; particularly around Docker image builds. Demonstrated knowledge of software applications and technical processes within a technical discipline (., cloud, artificial intelligence, machine learning, mobile, Preferred qualifications, capabilities, and skills Knowledge of table formats Iceberg. Knowledge of libraries Polars, PyIceberg . Knowledge of languages like Rust is a plus. Working knowledge in AWS and relevant cloud tools like Glue, Lambda