Data Engineer III

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Data Engineer III at JPMorgan Chase within the Commercial Investment Bank, 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

• Supports review of controls to ensure sufficient protection of enterprise data
• 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.
• Responsible for making configuration and customization changes to generate a product at business or customer requests and advising colleagues in requests
• Updates logical or physical data models based on new use cases
• Frequently uses SQL and understands NoSQL databases and their niche in the marketplace
• 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

• Formal training or certification on data engineering concepts and 3+ years applied experience
• Experience across the data lifecycle
• 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., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
• Advanced SQL skills (e.g., joins and aggregations) and working understanding of NoSQL databases
• Significant experience with statistical data analysis and able to determine appropriate tools and data patterns to perform analysis
• Experience customizing changes in tools to generate product outputs

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