Job Description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III - Data Engineer at JPMorgan Chase within the Asset and Wealth Management Technology and 55ip team, your role involves taking part in building its research data platform. You are responsible in implementing effective large-scale data solutions in a cloud-based environment.

Job responsibilities

• Build high-performance cloud-based data solutions to support quantitative research capabilities: back testing, simulations, machine learning, and other advanced analytics & algorithms
• Implement, schedule, and oversee ETL, ELT, and monitoring processes
• Oversee the loading of data from vendor and internal data sources
• Implement and support automation solutions to improve platform scalability
• Monitor the system performance by performing regular tests, troubleshooting, and integrating new features
• Provide L2 support for data systems to stakeholder teams
• Collaborate with technical teams to design and implement data solutions
• Recommend solutions to improve new and existing data systems
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience

• Bachelor's degree in information systems, information technology, computer science, or similar.

• Expertise in Structured Query Language (SQL), with strong Experience with AWS Cloud services/technologies, such as RDS, S3, Lambda, Secrets Manager
• Strong Experience in Python, Pandas/Polars, and Numpy, and clear understanding of OOP and software design constructs within a Python context
• Strong Experience in all aspects of software development lifecycle, especially Agile Scrum, along with experience in implementing and monitoring ETL processes

• Strong Experience with database technologies, architecture, performance tuning, and scaling along with strong experience in database design and modeling, experience with Airflow or similar orchestration tools

• Experience working with Data Lakes (Iceberg/Delta Table) and experience working with Spark and EMR along with experience working with CI/CD tools for application and database development

• Excellent communication (written and oral) and presentation skills, with agility: able to shift gears and react quickly to timely requests

• Ability to work with quant researchers & developers to understand requirements, strong attention to detail, pride in delivering high quality work and willingness to learn

• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.

• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

• Experience working with DuckDB is a plus
• Experience with PostgreSQL specifically is a plus
• Experience supporting development of AI/ML models
• Exposure to financial capital markets data and trading applications, working with investment data

• AWS certifications are a plus

• Experience with project workflow tools such as Jira in an Agile-Scrum environment

• Knowledge of Linux and knowledge of Docker