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In office (Jersey City, Wilmington)
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Staff
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Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 9, 2026. JPMorganChase scores A on the Alion truth index.

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JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

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.

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.

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