Mid-Level
Data Engineer III - Python / SQL
Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.
As a Data Engineer III at JPMorganChase within the Consumer & Community Banking - Data Technology team, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
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Supports review of controls to ensure sufficient protection of enterprise data
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Uses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
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Advises and makes custom configuration changes in one to two tools to generate a product at the business or customer request
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Updates logical or physical data models based on new use cases
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Frequently uses SQL and understands NoSQL databases and their niche in the marketplace
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Adds to team culture of diversity, opportunity, inclusion, and respect
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Applies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations.
Required qualifications, capabilities, and skills
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Formal training or certification on data engineering concepts and 3+ years applied experience
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Solid working experience with Python and Databricks
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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.
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Ability to review and validate AI-assisted outputs (e.g., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
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Experience across the data lifecycle
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Advanced at SQL (e.g., joins and aggregations)
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Working understanding of NoSQL databases
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Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis
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Experience customizing changes in a tool to generate product
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Must have strong analytical skills
Required qualification, capabilities, and skills
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AI/ML certifications
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AWS certifications
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