Location
London

Hours
Full Time

Salary
Competitive salary commensurate with experience

About the Role
Are you ready to shape the future of data engineering at JPMorgan Chase? Join a dynamic team where your unique skills will help build innovative solutions and contribute to a winning culture. You'll have opportunities for career growth, collaborate with talented professionals, and make a real impact on our business objectives. Your expertise will empower our teams and drive success across the firm.

As a Data Engineer within our agile team, you will design and deliver reliable data collection, storage, access, and analytics solutions that are secure, stable, and scalable. You will develop, test, and maintain essential data pipelines and architectures, supporting various business functions to achieve the firm's goals. Working with us, you will use your skills to drive innovation and help shape our team culture. Together, we focus on excellence, collaboration, and continuous improvement.

Key responsibilities include:
- Developing workflows and ELT pipelines using Python and Databricks
- Using enterprise-authorized AI capabilities to accelerate data pipeline design, analysis, and documentation while validating outputs and handling data according to sensitivity and security requirements
- Supporting review of controls to ensure sufficient protection of enterprise data
- Implementing data security using entitlements frameworks
- Updating logical or physical data models based on new use cases
- Frequent use of SQL and understanding of NoSQL databases
- Applying reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines, ensuring traceability, auditability, and alignment to resiliency and security expectations

Experience
- Formal training or certification on software engineering concepts with at least 3 years of applied experience
- Good working knowledge of AWS, Databricks, and Python
- Experience across the data lifecycle
- Demonstrated experience using enterprise-authorized AI capabilities to support data engineering workflows with strong validation habits and awareness of data sensitivity
- Ability to review and validate AI-assisted outputs before use, escalating when uncertain and following data handling requirements
- Advanced SQL skills including joins and aggregations
- Working understanding of NoSQL databases
- Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns for analysis
- Utilization of AWS Cloud Services for developing, deploying, and managing applications at scale
- Good understanding and working knowledge of software development lifecycle tools used for configuration management, CI/CD pipelines, unit testing, regression testing, and performance testing

Preferred Qualifications
- Familiarity with Standardized data layer practices (Medallion architecture)
- Exposure to Aurora Postgres and MongoDB
- Skills in designing efficient data models including normalization, denormalization, and schema design with understanding of relational and star schemas

About You
You are a motivated and detail-oriented professional who thrives in a collaborative, fast-paced environment. You have a strong commitment to data security and quality, and you embrace continuous learning and innovation. You value teamwork and are eager to contribute to a culture of excellence and continuous improvement.

Qualifications
Formal training or certification in software engineering or related fields is required. Proven experience and skills as outlined above are essential to succeed in this role.