Principal Data Engineer (AWS, Databricks, Ai, ML Flow, Data Architecture, Apache Airflow)

Mastercard Foundry R&D is seeking a Principal Data Engineer to design and build the data foundations powering advanced analytics, machine learning, generative AI, and agentic AI solutions.

You will lead the architecture, design, and engineering of scalable data platforms, collaborating with AI Engineers, Data Scientists, and Product Managers to turn ambiguous R&D objectives into secure, scalable, and production-ready data systems.

• Lead the architecture, design, and engineering of scalable batch, streaming, and event-driven data platforms
• Design and build reliable data ingestion, transformation, enrichment, processing, and consumption pipelines
• Develop governed lakehouse and modern data platform architectures using cloud-native technologies
• Enable the full AI and machine learning lifecycle through robust feature engineering, training, evaluation, deployment, and inference pipelines
• Define engineering standards for data modeling, software development, testing, CI/CD, and observability
• Provide hands-on technical leadership through architecture reviews, code reviews, troubleshooting, and engineering mentorship

• 12-18 years of overall relevant experience, including ownership of complex enterprise data engineering solutions
• Expert programming skills in Python, PySpark, and modern software engineering practices
• Advanced SQL expertise, including data modeling, performance tuning, and query optimization
• Strong hands-on experience with Apache Spark and modern lakehouse platforms
• Experience building and operating cloud-native data platforms in AWS or Azure
• Experience with workflow orchestration platforms such as Apache Airflow or Databricks Workflows
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical discipline, or equivalent practical experience