Sr. Lead Software Engineer: Data Engineering

Embrace this pivotal role as an essential member of a high performing team dedicated to reaching new heights in data engineering.

Your contributions will be instrumental in shaping the future of one of the world's largest and most influential companies.

As a Senior Lead Data Engineer at JPMorganChase within the Employee Data Technology, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way.

Leverage your deep technical expertise and problem solving capabilities to drive significant business impact and tackle a diverse array of challenges that span multiple data pipelines, data architectures, and other data consumers.

Job responsibilities



* Provides recommendations and insight on data management and governance procedures and intricacies applicable to the acquisition, maintenance, validation, and utilization of data


* Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and design analysis and technical documentation, validating outputs and handling data according to sensitivity and security requirements.


* Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way


* Defines database back-up, recovery, and archiving strategy


* Generates advanced data models for one or more teams using firmwide approaches, linear algebra, statistical and geometrical algorithms


* Approves data analysis tools and processes


* Creates functional and technical documentation supporting best practices


* 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


* Evaluates and reports on access control processes to determine effectiveness of data asset security


* Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., validation automation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.

Required qualifications, capabilities, and skills



* Formal training or certification on data engineering concepts with architecture and production ownership concepts and 5+ years applied experience


* Hands-on practical experience delivering system design, application development, testing...