Data Engineer I - Global Commercial Services

Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues.

The Technology organization enables and accelerates the companys growth strategies, delivering global capabilities and services in support of Amexs customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights.

Global Commercial Services (GCS) serves millions of business customers around the world, from mom-and-pop shops to approximately 70% of the S&P 500. We are the number one issuer of small business cards, the industry leader in corporate T&E and represent approximately 40% of the companys total revenues. Our vision is to be essential to our customers businesses every day. We do that by offering a diverse suite of payment and cashflow tools our customers need to run and grow their businesses, from a wide range of traditional card products, to working capital and supply chain financing, to new digital solutions that make it easy for our customers to manage their financial and payment needs.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, youll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

• Bachelors or Masters degree in Computer Science, Engineering, or related field
• Strong programming skills in Python and experience with Apache Spark
• Proven experience building reliable ETL/ELT pipelines in production environments
• Hands-on experience with data quality frameworks
• Experience implementing data governance principles (cataloging, lineage, metadata management, access control)
• Familiarity with cloud data platforms (AWS, Azure, or GCP)
• Strong understanding of data modeling, schema evolution, and data lifecycle management
• Experience supporting ML pipelines with a focus on data validation, feature stores, and reproducibility

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.

• Design and build scalable, fault-tolerant data pipelines using Apache Spark and Python
• Establish and enforce data governance frameworks, including data quality rules, lineage, cataloging, and access controls
• Implement data reliability practices such as validation checks, anomaly detection, SLAs/SLOs, and automated alerting
• Develop and maintain automated data workflows using orchestration tools (e.g., Airflow)
• Partner with stakeholders to define data contracts, schemas, and standards across domains
• Enable end-to-end observability of data pipelines (freshness, completeness, accuracy)
• Support machine learning pipelines, including feature engineering, training data validation, and monitoring model input/output data quality
• Document data assets, lineage, and governance policies to improve discoverability and trust
• Design and build scalable, fault-tolerant data pipelines using Apache Spark and Python
• Establish and enforce data governance frameworks, including data quality rules, lineage, cataloging, and access controls
• Implement data reliability practices such as validation checks, anomaly detection, SLAs/SLOs, and automated alerting
• Develop and maintain automated data workflows using orchestration tools (e.g., Airflow)
• Partner with stakeholders to define data contracts, schemas, and standards across domains
• Enable end-to-end observability of data pipelines (freshness, completeness, accuracy)
• Support machine learning pipelines, including feature engineering, training data validation, and monitoring model input/output data quality
• Document data assets, lineage, and governance policies to improve discoverability and trust