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 Responsibilities

• Executes 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 Skills

• Formal 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

• Experience 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