Job Description

The Colleague Experience Group (CEG) is responsible for delivering colleague-focused programs and services globally, including career growth and development, leadership and learning, recruitment, colleague servicing, and other employee experience initiatives.

Within CEG, the Colleague Services (CS) organization enables colleagues through best-in-class services, capabilities, knowledge, and operational support, empowering them to perform at their best.

The Colleague Data Office is responsible for advancing data governance, data quality, and data risk management across CEG. The team partners closely with Business, Technology, Risk, and Enterprise Data Management teams to strengthen the data control environment, improve data quality, and ensure data is managed as a strategic enterprise asset.

• Design, develop, and optimize scalable data pipelines and curated datasets using Enterprise Data Platform (EDP) capabilities to enable self-service analytics and enterprise reporting.
• Partner with Product Owners, Agile teams, and business stakeholders to translate business requirements into reusable data products, semantic datasets, and reporting solutions.
• Develop analytical solutions, dashboards, and reporting capabilities using SQL, BigQuery, Python, and Power BI to support business decision-making and operational insights.
• Build and maintain data models, transformations, and data integration processes that improve accessibility, consistency, and usability of enterprise data.
• Collaborate with upstream and downstream application teams to understand data flows, integrate new data sources, and ensure reliable end-to-end data delivery.
• Support User Acceptance Testing (UAT), validation, and deployment of new data products, reporting enhancements, and pipeline improvements within the Enterprise Data Platform.
• Monitor and improve data pipeline performance, data quality, and operational reliability through automation, validation, and continuous improvement practices.
• Perform root cause analysis on data and reporting issues, identify underlying process or system gaps, and implement sustainable corrective solutions.
• Identify and document Critical Data Elements (CDEs), data lineage, metadata, and business definitions to improve discoverability and trust in enterprise data assets.
• Implement and monitor appropriate data quality controls, governance standards, and metadata practices to ensure trusted and compliant data products.
• Support data governance, data stewardship, and data risk remediation activities as part of the overall data product lifecycle.
• Participate in Agile ceremonies including sprint planning, stand-ups, sprint reviews, and retrospectives to support iterative delivery and continuous improvement.
• Collaborate with Business, Technology, Data Engineering, and Enterprise Data Office teams to continuously enhance EDP capabilities and self-service data solutions.

• 4–6 years of experience in data engineering, data analytics, business intelligence, enterprise data platforms, or a related discipline.
• Strong proficiency in SQL for developing complex queries, data transformations, and high-performance datasets.
• Hands-on experience with Python for data engineering, automation, scripting, and data validation.
• Experience working with Google BigQuery or similar cloud data warehouse technologies to build scalable data pipelines and analytical datasets.
• Experience developing Power BI / Tableau dashboards, semantic models, and self-service reporting solutions.
• Experience designing and supporting data pipelines, ETL/ELT processes, and enterprise reporting solutions using modern cloud data platforms.
• Strong understanding of data modeling, data integration, and data lifecycle management principles.
• Ability to translate business requirements into scalable data products and reporting capabilities.
• Strong analytical and problem-solving skills with experience diagnosing data issues and implementing sustainable solutions.
• Experience working in Agile teams with cross-functional business and technology stakeholders.

Preferred Qualifications

• Bachelor’s degree in computer science, Information Systems, Data Engineering, Data Analytics, Engineering, or a related field.
• Experience working with Enterprise Data Platforms (EDP), modern data lakes, or cloud-native analytics platforms.
• Knowledge of data governance concepts including metadata management, data lineage, data quality, and stewardship.
• Experience with enterprise metadata or data catalog tools.
• Exposure to data governance, data risk, and regulatory requirements within enterprise environments.
• Experience building reusable data products that enable self-service analytics and business reporting.
• Prior experience supporting HR, employee, or enterprise operational data domains is an advantage.

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.