Mastercard
FinTech
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Mastercard. Skills: Data engineering, Machine learning, Data warehousing, Cloud data platforms. Design data pipelines. Build data models”
Industry & Context.
Data analysis; Troubleshooting; Optimization
What They're Looking For.
Must Have
Bachelor's degree in Statistics, Computer Science, Mathematics, or related field, 5+ years of experience in data engineering or related roles, Proficiency in SQL, Experience with Python or Scala, Experience with cloud data platforms (e.g., AWS, GCP, Azure)
Nice to Have
Master's degree or PhD in a quantitative field, Experience with distributed data processing frameworks (e.g., Spark), Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift), Experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch), GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification
What You'll Do.
Design data pipelines
Develop ETL processes
Manage data warehouses
Implement machine learning models
Perform statistical analysis
Create business intelligence solutions
Engineer analytics solutions
Conduct quantitative analysis
Optimize data infrastructure
Collaborate with stakeholders
How You'll Work.
Team & Collaboration
Cross-functional teams; Data scientists; Analysts; Product managers
Full Job Description
**Our Purpose** _Mastercard powers economies and empowers people in 200 + countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential._ **Title and Summary** ### Senior Data Engineer ### About the Role As a Senior Data Engineer, you’ll take ownership of building and optimizing data platforms, pipelines, and systems that enable advanced analytics, machine learning, and business insights. You’ll collaborate closely with engineering, product, and analytics teams to deliver reliable, production-ready data solutions. Role •Design, build, and maintain scalable data platforms leveraging Data Engineering best practices •Develop and optimize large-scale data pipelines using Distributed Data Processing frameworks •Implement and manage automated workflows using Workflow Orchestration to ensure reliable data movement and processing •Design and integrate data from multiple sources using Data Integration techniques to create a unified, accessible data layer •Build and maintain scalable Data Lakes for storing and analyzing large, diverse datasets •Define and implement robust Data Modeling strategies to support analytics and reporting use cases •Design and optimize Database Design solutions to ensure performance, scalability, and data integrity •Process and transform large datasets using efficient Data Processing techniques to generate actionable insights •Ensure strong Data Security practices, including data protection, governance, and compliance •Lead system design discussions and contribute to architectural decisions •Own full SDLC delivery including requirements, design, development, testing, and deploymen
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