Data Engineer II - Global Servicing Technology

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 company's growth strategies, delivering global capabilities and services in support of Amex's 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.

The Servicing Experiences Technology (SET) organization enhances Servicing Experiences by building smarter platforms with seamless automation and AI-driven insights- empowering Colleagues and Customers alike.

The Data Platform team is seeking a Data Engineer who is comfortable operating in a modern, enterprise-scale data platform with a strong emphasis on building reliable, scalable data pipelines and enabling analytics at scale. The ideal candidate will be responsible for designing, building, and maintaining data systems that support critical business and operational use cases.

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, you'll 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.

• 2-5 years of experience in data engineering or backend engineering.
• Strong proficiency in Python, Java and SQL.
• Experience building and maintaining ETL/ELT pipelines in cloud environments (GCP preferred).
• Hands-on experience with Airflow (or similar tools) and distributed processing frameworks.
• Understanding of data modeling and distributed systems concepts.
• Experience with data quality, validation, and monitoring practices.
• Exposure to event-driven systems such as Kafka.
• Strong problem-solving skills and ability to work independently with limited guidance.
• Some hands-on experience building or contributing to AI-powered features, LLM-based applications, or applied ML systems (professional or project-based).

Preferred Qualifications

• Experience with data warehousing platforms (BigQuery or similar).
• Familiarity with streaming architectures and real-time data processing.
• Experience working in large-scale or regulated enterprise environments.
• Exposure to analytics/BI tools (Tableau, Power BI, Looker).
• Experience optimizing large datasets and high-throughput pipelines.
• A track record of shipping AI-powered or agentic systems that real users depend on.
• Hands-on experience with modern LLM tooling and agentic patterns and architectures.
• Fluency with AI-assisted and agentic development workflows.

AI-Assisted Development

• Familiarity with AI-assisted development tools for coding, testing, and optimization.
• Ability to apply these tools pragmatically while maintaining production-grade engineering standards.

Enterprise Expectations

• Strong ownership mindset with the ability to connect across systems and architectures.
• Demonstrated ability to collaborate across teams and drive alignment.
• Clear communication and documentation skills.
• Commitment to building systems that meet high standards for reliability, scalability, security, and auditability.
• Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
• Build and maintain scalable data pipelines (batch and streaming).
• Ingest, transform, and model data for analytics and operational use cases.
• Ensure data quality and reliability through validation, monitoring, and alerting.
• Integrate with upstream systems and downstream data platforms and BI tools.
• Optimize data pipelines for performance, scalability, and cost efficiency.
• Implement data governance practices, including lineage and auditing.
• Own production workflows, including availability, latency, and failure recovery.
• Test, troubleshoot, and debug data pipelines and processes.
• Write efficient SQL queries to extract and manipulate data across relational and analytical systems.
• Apply data quality and QA testing methodologies to ensure accuracy and consistency.
• Demonstrate understanding of data risk management and compliance best practices.
• Collaborate effectively across teams to deliver data-driven solutions.
• Manage complex systems with multiple stakeholders and dependencies.
• Contribute to software delivery lifecycle processes including build, test, deployment, and operations.
• Build and maintain scalable data pipelines (batch and streaming).
• Ingest, transform, and model data for analytics and operational use cases.
• Ensure data quality and reliability through validation, monitoring, and alerting.
• Integrate with upstream systems and downstream data platforms and BI tools.
• Optimize data pipelines for performance, scalability, and cost efficiency.
• Implement data governance practices, including lineage and auditing.
• Own production workflows, including availability, latency, and failure recovery.
• Test, troubleshoot, and debug data pipelines and processes.
• Write efficient SQL queries to extract and manipulate data across relational and analytical systems.
• Apply data quality and QA testing methodologies to ensure accuracy and consistency.
• Demonstrate understanding of data risk management and compliance best practices.
• Collaborate effectively across teams to deliver data-driven solutions.
• Manage complex systems with multiple stakeholders and dependencies.
• Contribute to software delivery lifecycle processes including build, test, deployment, and operations.