Year-Round Intern - Data

The OCC•Chicago, IL

12h•Hybrid

About The Position

The OCC Internship Program equips students with the real-world skills needed to transition successfully into a career in financial services. As an intern, you will contribute to meaningful projects, applying your skills and knowledge to real challenges facing the business. Your time with us is a real opportunity to make a genuine impact on the future of OCC! OCC's Year-Round Internship Program is a 12-month opportunity running from January through December and is open to both undergraduate and graduate students who are actively enrolled at a college or university. Interns work up to 20 hours per week during the school year and up to 40 hours per week during the summer, subject to a 1,000-hour cap. The role is based in a hybrid work environment, and overtime is not permitted. The intern will work closely with Data Platform Core and Data Services teams. These teams are responsible for building and maintaining foundational cloud-based data processing and data access capabilities and services using stream processing technologies such as SQL, REST-based APIs, Java Spring Boot, Python, Kubernetes, Kafka. The intern will get more familiar with continuous integration and continuous deployment technologies such as Git Jenkins, and Artifactory, and DevOps concepts and tools; infrastructure and application monitoring tools and technologies such Splunk.

Requirements

Rising senior or second-year graduate student, graduating December 2027 or May/August 2028.
Desired Majors: Computer Science, Information Systems, Data Analytics
Desired Knowledge of SQL; data analytics skills; Python and/or Java programming skills
Demonstrated intellectual curiosity and a strong desire to learn fast; ability to ramp up quickly in large codebases, absorb new technologies, and deliver meaningful contributions in a short period of time.
Foundational understanding of distributed systems concepts such as message delivery semantics, basic fault-tolerance patterns, and event-driven architecture, with enthusiasm to deepen this knowledge on the job.
Some hands-on cloud experience, preferably with AWS services such as S3, IAM, or EC2, with a willingness to develop production-level cloud-native skills including networking, security, and high-availability design.
Capacity to stay composed and focused under pressure in time-sensitive production situations, with a desire to develop operational maturity across SLA adherence, data correctness, and system availability.
Genuine openness to adopting AI-assisted engineering workflows such as Claude Code as part of daily development, with curiosity about how intelligent tooling can improve developer productivity and code quality.
Clear written and verbal communication skills, with the ability to ask good questions, document work thoroughly, and participate productively in technical discussions with peers and stakeholders.
A team-first mindset with the ability to work constructively with business, technical, and non-technical professionals in a fast-paced agile environment, and a proactive approach to problem-solving.

Responsibilities

Work closely with Data Platform Core and Data Services team responsible for foundational cloud-based data processing and data access capabilities and services using stream processing technologies such as SQL, Java Spring Boot, Python, Kubernetes, Kafka.
Collaboratively work with the members of the team on planning, documenting requirements, writing SQL code, and troubleshooting issues.
Learn new tools to tools and technologies.
Participate in sprint reviews and present end of the sprint, deliverables.
Leverage AI-assisted development tools, including Claude Code, to accelerate feature development, test generation, code review, and documentation while building good engineering habits in a regulated environment.
Collaborate with business users and technical teams across the organization to understand data needs, gather requirements, and contribute to solutions that make internal data accessible and useful for analysts.