Lead Software Engineer- Python / Big Data / AWS/ ETL Pipelines

Lead Software Engineer 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 JPMorganChase within the Corporate Sector, Corporate Technology, 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 ResponsibilitiesExecutes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others Defines and drives the technology roadmap, focusing on next-generation data, analytics, and automation platforms Leads the adoption and integration of cutting-edge technologies including Databricks, Snowflake, AWS, and modern web frameworks Architects scalable, secure, and resilient solutions for valuation control, pricing, and regulatory compliance Champions the use of AI, machine learning, and advanced analytics to deliver real-time risk insights and anomaly detection Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Designs and implements data pipelines, analytics workflows, and reporting solutions using Python, Databricks, and Spark Develops and maintains web-based applications and dashboards for valuation and risk management using modern web stacks (React, Angular, etc.) Builds and optimizes data models, ETL/ELT processes, and integration frameworks for large-scale financial data Ensures data quality, security, lineage, and governance across all team platforms Required Qualifications, Capabilities, and SkillsFormal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Hands-on expertise in Python, Databricks, Spark, and data pipeline development Strong knowledge of cloud platforms (AWS, Azure, GCP) and data warehousing solutions (Snowflake, Databricks) Advanced proficiency in designing scalable, secure, and resilient systems for large-scale data environments Demonstrated ability to lead engineering teams, set technical direction, and deliver complex projects Demonstrated experience in leading and implementing standard software engineering practices, such as Agile development, code reviews, automated testing, CI/CD pipelines, and documentation Experience with data cataloging, metadata management, and data discovery tools (e.g., Collibra, Atlan, AWS Glue, Databricks Unity Catalog), including implementation and integration into enterprise platforms Proficiency in automation and continuous delivery methods Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Preferred Qualifications, Capabilities, and SkillsExperience with AI / BI Tools and modern web development frameworks (React, Angular, etc.) Deep understanding of AI, machine learning, and advanced analytics techniques, with practical experience implementing ML models in production Proven experience in financial markets, risk management, or valuation control functions Exposure to vendor-based financial software solutions and integration