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# Lead Data Engineer - Snowflake/Python/AWS

- **Company:** JPMorgan Chase & Co.
- **Location:** Jersey City, NJ, United States
- **Experience:** Expert
- **Salary:** $147,250.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, HTML, JavaScript (Programming Language), Amazon Web Services, Business Analytics Applications, Cloud Foundry, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Platform as a Service (PAAS), Cloud Services, Software Configuration Management, Software Deployment, SQL Databases, Web Applications, Web Application Frameworks, Snowflake, Front End Software Development, Data Pipelines
- **Published:** August 20, 2026
- **Apply:** https://www.juju.com/job/00000000go0s3t

## About the Role

Qualifications: hands-on Python data engineering experience at scale, experience deploying applications on Cloud Foundry or equivalent PaaS platforms, proficiency in SQL and cloud data warehouse platforms, experience with enterprise CI/CD tooling and application governance, and comfort building front-end interfaces through Python web frameworks. Strong communicator comfortable working with senior stakeholders to translate business requirements into scalable data products.

## Description

As a Lead Data Engineer at JPMorgan Chase, 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, data models, and application infrastructure across multiple programs in support of the firm's business objectives., Responsibilities include building and maintaining Python-based ETL pipelines and data transformations sourcing from cloud data platforms, owning the deployment and release pipeline for cloud-hosted web applications including CI/CD onboarding and repository management, designing and maintaining SQL views and data models powering executive-facing dashboards and LOB reporting, building lightweight HTML/JavaScript front-ends served through Python web frameworks, serving as Application Owner responsible for compliance posture and platform health, and driving the migration of existing reporting workflows off legacy tools toward scripted, version-controlled equivalents.


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