at J.P. Morgan
Bulge Bracket Investment BanksPosted 7 days ago
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**Data Engineer III** - JPMorganChase, Buenos Aires. Design and deliver trusted, secure, and scalable data solutions, serving as a seasoned agile team member. **Responsibilities**: Enhance data protection, use AI for pipeline optimization, customize tools for business requests, and update data models. **Required**: 3+ years of data engineering experience, advanced SQL skills, NoSQL understanding, statistical data analysis experience, and strong English proficiency. Prioritize enterprise-authorized AI use, validate AI-assisted outputs, and maintain quality routines.
- Compensation
- Not specified
- City
- Not specified
- Country
- Argentina
Currency: Not specified
Full Job Description
Location: Ciudad Autnoma de Buenos Aires, Argentina
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 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 firms 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
- Advanced English skills
