Job
Description
You have the opportunity to unleash your full potential at a world-renowned company and take the lead in shaping the future of technology. As a Senior Manager of Data Engineering at JPMorgan Chase within the Asset and Wealth management, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as we'll as anticipate the needs and potential dependencies of other data users within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities. 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 . In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise 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 (eg, cloud, artificial intelligence, machine learning, etc) 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 like Airflow Preferred qualifications, capabilities, and skills Knowledge of table formats i.e Iceberg. Working knowledge in AWS and relevant cloud tools like Glue, Lambda
