Campus Graduate Masters Summer Internship Program - 2027 Data Engineer, Enterprise Technology Services- Phoenix, AZ

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. At American Express, we empower technologists to learn, innovate, and make an impact from day one. As a Data Engineer Intern in Enterprise Technology Services, you’ll contribute to data engineering initiatives that help teams build reliable, scalable, secure, and well-governed data solutions. Data Engineer Intern help make data available, trustworthy, and useful for business, product, analytics, and technology teams. In this role, you may work with data requirements, data models, data pipelines, database systems, Big Data patterns, cloud-native data tooling, production support, data quality, and data governance practices while collaborating with engineers, product partners, architects, data practitioners, and business stakeholders. Responsibilities & What Type of Work to Expect Support the design, development, testing, and improvement of data pipelines, database infrastructure, and integration patterns. Review data requirements, sources, flows, mappings, and models to help align data solutions with data architecture and business needs. Assist with database development and support across relational, non-relational, NoSQL, Big Data, and cloud-native data platforms. Apply foundational data engineering concepts such as partitioning, indexing, storage patterns, data quality checks, performance tuning, and scalable processing under guidance. Collaborate with product, business, architecture, analytics, and engineering partners in an Agile team environment. Support monitoring, observability, troubleshooting, documentation, data preparation, and continuous improvement activities that strengthen data quality and pipeline reliability. Contribute to data modeling, ETL, data validation, source-to-target documentation, and data maintenance practices. Follow engineering, data governance, privacy, security, and documentation practices to help protect sensitive information and support responsible data use. Minimum Qualifications Currently enrolled in a full-time Master’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 including data structures, algorithms, debugging, testing, and problem solving. Familiarity with data requirements, data models, data pipelines, database systems, storage formats, and architecture patterns that support business and product goals. Demonstrated interest in data engineering, databases, data platforms, analytics, cloud data tooling, Big Data, or software engineering. Strong communication, collaboration, organization, attention to detail, and learning agility with the ability to work effectively in a team environment. Preferred Qualifications Master’s degree candidates with an expected graduation date between December 2027 and June 2028. 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, NoSQL, 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-tier architectures, scalable storage patterns, online transaction processing, online analytical processing, and production support concepts. Exposure to data modeling, data preparation, ETL, data validation, lineage, documentation, access patterns, and data quality practices. Interest in data preparation practices that support analytics, business intelligence, reporting, operational insights, or data-driven decision-making. Familiarity with Agile, Scrum, Test-Driven Development, CI/CD, version control, code reviews, or related software delivery practices. Awareness of data governance principles, including validation, privacy, lineage, data quality, security, and protection of sensitive information. Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and will contact qualified candidates regarding next steps. Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.