Big Data AWS Lead Software Engineer

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team

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 Consumer & Community Banking Digital Personalization & Insights team, 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 breakdown technical problems Develops secure and high-quality production code, and reviews and debugs code written by others Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Design & build new applications utilizing leading edge technologies and modernize existing applications Implement batch & real-time software components consistent with architectural best-practices of reliability, security, operational efficiency, cost-effectiveness and performance Hands on application development (Python) leveraging distributed compute such as Apache Flink or Apache Spark on very large datasets Design and development of applications that leverage the AWS infrastructure deploying software components on AWS using common compute and storage services such as EC2, EKS, and Lambda, S3 Lead and deliver projects from concept to production across PNI (Personalization and Insights) platform and provide level 2 support for production systems 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 Advanced in one or more programming language(s) Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices 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 Python, Apache Spark, Apache Flink or similar large-scale data processing engines Experience with Distributed Datastores (e.g. Cassandra, Red Shift) Strong experience designing, developing and deploying software components on AWS using common compute and storage services such as EC2, EKS, Lambda, S3 Strong experience with Big Data / Distributed / cloud technology (AWS Big data services like lambda, glue, glue emr, Performance tuning, Streaming, KAFKA, Entitlements etc., ) Preferred qualifications, capabilities, and skills Experience building ETL/Feature processing pipelines Experience using workflow orchestration tools—Airflow, Kubeflow etc. Experience using Terraform to deploy infrastructure-as-code to public cloud Experience with Linux scripting such as Bash, KSH, or Python Certified AWS Cloud Practitioner, Developer or Solutions Architect strongly preferred