Lead Software Engineer- Python Big Data AWS ETL Pipelines

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

As a Lead Software Engineer at JPMorganChase within the Corporate Sector Corporate Technology youare 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 firms 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