Campus Undergraduate Summer Internship Program

JOB DESCRIPTION
Business Unit / Role Specific Info The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company. As a Data Engineer Intern in Enterprise Technology Services, you’ll join a 10-week Summer Internship Program and contribute to real-world data engineering initiatives that help teams build reliable, scalable, and well-governed data solutions. Data Engineers help make data available, trustworthy, and useful for business, product, analytics, and technology teams. In this role, you may support data requirements, data modeling, data pipelines, database systems, big data patterns, cloud-native data tooling, and production support activities with guidance from peers and leaders. You’ll gain exposure to data architecture, database systems, modern data platforms, data pipelines, and agile engineering practices. You’ll collaborate with engineers, product partners, data practitioners, architects, and business stakeholders to learn how enterprise data systems are designed, developed, documented, supported, monitored, and continuously improved. Enterprise Technology Services teams build and support technology that enables trusted, secure, and customer-first experiences across American Express. Data Engineering teams help design, integrate, optimize, and maintain the systems and pipelines that move data across platforms and products. As a Data Engineer Intern, you’ll contribute at an early career level while learning how data requirements, architecture, database infrastructure, Agile delivery, data quality, lineage, governance, and responsible AI-enabled engineering practices come together in an enterprise environment. Review data requirements, sources, flows, and models with guidance to support integration and alignment with data architecture. Support the design, development, testing, and improvement of data pipelines, database infrastructure, and integration patterns. Assist with database development and support across relational, non relational, NoSQL, Big Data, and cloud native data platforms Apply foundational Big Data concepts such as partitioning, indexing, storage patterns, performance tuning, and scalable processing under guidance. Collaborate with product, business, architecture, and engineering partners in an Agile team while following development and documentation standards. Use AI enabled tools for development, troubleshooting, documentation, testing, and code validation while validating AI generated recommendations before implementation. Support monitoring, observability, data preparation, and continuous improvement activities that strengthen pipeline reliability, data quality, and engineering productivity. Currently enrolled in a full-time Bachelor’s degree program in Computer Science, Computer Engineering, Information Systems, Data Engineering, Data Science, Engineering, or another technical field. Foundational knowledge of SQL and at least one programming language such as Python or Java. Foundational understanding of computer science concepts such as data structures, algorithms, debugging, testing, and problem-solving. Familiarity with data requirements, models, pipelines, database systems, storage formats, and architecture patterns support business and product goals. Demonstrated interest in data engineering, databases, data platforms, analytics, cloud data tooling, Big Data, or software engineering. Bachelor’s degree candidates with an expected graduation date between December 2027 and June 2028. Coursework, projects, internships, hackathons, research, or extracurricular experience involving SQL, Python, Java, data pipelines, databases, APIs, analytics, or data engineering concepts. Knowledge of relational and non-relational database concepts such as data modeling, indexing, partitioning, replication, high availability, encryption, performance tuning, and data maintenance. Familiarity with Big Data, SQL, or cloud-native data platforms such as HBase, Hive, MongoDB, Cassandra, Redis, Couchbase, BigQuery, Spanner, PostgreSQL, Oracle, MS SQL Server, DB2, or similar tools. Awareness of distributed systems, multi-tiered architectures, scalable storage patterns, online transaction processing, and online analytical proce