Lead Data Engineer - Python/PySpark/Databricks/AWS/AI

Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated.

Together we will create a brighter future and make a meaningful difference.

As a Lead Data Engineer - Python/PySpark/Databricks/AWS/AI at JPMorganChase within the Consumer & Community Banking , you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way.

As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities



* Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms


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


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


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


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


* Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., backup/recovery validation 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 Science engineering concepts and 5+ years applied experience


* Expertise with Python, PySpark, Databricks, Snowflake, AWS and AI


* Working experience with both relational and NoSQL databases


* Experience and proficiency across the data lifecycle


* Experience with database back-up, recovery, and archiving strategy


* Proficient knowledge of linear algebra, statistics, and geometrical algorithms


* Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.


* Ability to review and validate AI-assisted outputs (e.g., model/design summaries or operational checklists) before use, escalating when uncertain and following data handling requirements.

Preferred qualifications, capabilities, and skills



* Exposure to cloud technologies


* Hands-on experience on Kafka or any streaming technology


* Hands-on experience in Splunk, Dynatrace tools


* Exposure to AI Driven development

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their fin...