Senior Software Engineer II

Mastercard Mastercard · Fintech · O Fallon, MO +1 · Engineering

Mastercard is seeking a Senior Software Engineer II, who will be responsible for building and optimizing data platforms, pipelines, and systems to support advanced analytics, machine learning, and business insights. The role involves collaborating with engineering, product, and analytics teams to deliver reliable data solutions.

What you'd actually do

  1. Design, build, and maintain scalable data platforms leveraging Data Engineering best practices
  2. Develop and optimize large-scale data pipelines using Distributed Data Processing frameworks
  3. Implement and manage automated workflows using Workflow Orchestration to ensure reliable data movement and processing
  4. Design and integrate data from multiple sources using Data Integration techniques to create a unified, accessible data layer
  5. Build and maintain scalable Data Lakes for storing and analyzing large, diverse datasets

Skills

Required

  • Experience designing and building scalable systems using modern Data Engineering principles
  • Strong experience with Distributed Data Processing and large-scale data platforms
  • Hands-on experience with Data Integration, Data Modeling, and Data Processing
  • Experience building and maintaining Data Lakes and modern data architectures
  • Solid understanding of Database Design and data optimization techniques
  • Knowledge of Workflow Orchestration tools and end-to-end pipeline automation
  • Strong understanding of Data Security and data governance practices
  • Proven ability to work independently on complex technical challenges
  • Strong troubleshooting and root cause analysis skills in data environments
  • Experience working in Agile/Scrum environments and collaborating across teams
  • Strong communication and collaboration skills, with the ability to influence decisions
  • Experience mentoring or supporting other engineers
  • Bachelor’s degree or equivalent experience

Nice to have

  • Experience with cloud platforms (AWS, Azure, or GCP) and modern data tooling
  • Experience with event-driven or streaming architectures
  • Exposure to machine learning or advanced analytics environments
  • Experience in high-throughput or regulated environments (payments, banking, fintech)