Data Engineer – Marketing Optimization Capabilities & Analytics (MOCA)

About the Team

Marketing Optimization Capabilities & Analytics (MOCA) is an enterprise Marketing Mix Modeling (MMM) platform that enables American Express to measure and optimize the impact of marketing investments. MOCA separates short-term advertising-driven contributions from long-term business trends, external factors, and seasonal influences to provide actionable insights for marketing decision-making.

The platform models marketing drivers (inputs) and acquisition outcomes at the product, response channel, and DMA level on a weekly basis, helping leadership understand the effectiveness and ROI of enterprise marketing spend.

Role Summary

We are seeking a highly motivated Senior Data Engineer to join the MOCA team. This role will be responsible for designing, building, and maintaining scalable data pipelines and analytical data products that power enterprise-level Marketing Mix Modeling and marketing analytics capabilities.

The ideal candidate will have strong expertise in big data engineering, cloud technologies, data modeling, and large-scale ETL development. The role requires close collaboration with data scientists, product managers, marketing analytics teams, and business stakeholders to deliver reliable and scalable data solutions.

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.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines supporting MOCA and MMM workloads.
• Build and optimize batch and near-real-time data ingestion processes from multiple enterprise data sources.
• Develop and maintain data models supporting marketing analytics, attribution, experimentation, and reporting use cases.
• Partner with Data Science teams to operationalize Marketing Mix Models and analytical outputs.
• Design and implement data quality, monitoring, lineage, and governance frameworks.
• Build reusable data services, APIs, and datasets to support enterprise analytics and reporting.
• Optimize data processing performance, scalability, and reliability across large datasets.
• Collaborate with Product, Marketing, and Analytics teams to translate business requirements into technical solutions.
• Support cloud migration and modernization initiatives across the analytics ecosystem.
• Mentor junior engineers and promote engineering best practices.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
• 5+ years of experience in Data Engineering or related disciplines.
• Strong SQL skills and experience working with large-scale analytical datasets.
• Expertise in Python, Spark, Scala, or Java.
• Experience building enterprise-grade ETL/ELT pipelines.
• Strong understanding of dimensional modeling, data warehousing, and data architecture principles.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Experience with orchestration tools such as Airflow, Control-M, or similar platforms.
• Strong understanding of data quality, observability, and governance practices.
• Excellent communication and stakeholder management skills.
   

Preferred Qualifications

• Experience supporting Marketing Analytics, Customer Analytics, or Marketing Mix Modeling platforms.
• Experience working with large-scale customer acquisition and marketing datasets.
• Familiarity with machine learning operationalization and model deployment workflows.
• Experience with enterprise experimentation and measurement platforms.
• Experience with modern data lake and data mesh architectures.
• Experience leading technical initiatives and mentoring engineering teams.
   

What Success Looks Like

• Deliver scalable and reliable data pipelines supporting MOCA and MMM capabilities.
• Improve data quality, performance, and operational efficiency.
• Enable faster and more accurate marketing investment decisions through high-quality data products.
• Drive modernization and automation initiatives across the analytics ecosystem.
• Serve as a trusted technical partner for Data Science, Product, and Business stakeholders.
   

Key Technologies

• SQL
• Python
• Spark / PySpark
• Hadoop / Big Data Ecosystem
• Airflow
• Cloud Platforms (AWS / Azure / GCP)
• Data Warehousing
• ETL / ELT Frameworks
• Git / CI-CD
• Analytics & Reporting Platforms