Mastercard is hiring a Senior Data Engineer to build scalable data platforms for analytics and insights products. The ideal candidate combines data engineering fundamentals with a platform mindset and takes pride in building systems that other teams depend on.
Requirements
- Design, build, and maintain scalable data pipelines and platform services that support multiple product teams.
- Develop reusable patterns for data ingestion, transformation, and serving, prioritizing reliability, consistency, and ease of adoption.
- Build and improve services for customer data onboarding, ensuring strong controls around security, isolation, and governance.
- Contribute to the development of data and AI platform capabilities that support analytics, machine learning, and emerging intelligent applications.
- Translate business and product requirements into well-designed data architectures and pipeline solutions.
- Implement batch and streaming data workflows using modern cloud data technologies (e.g., Spark, Databricks, Airflow, cloud-native storage).
- Apply best practices for data modeling, schema management, and pipeline performance optimization.
- Ensure systems are designed with scalability, maintainability, and cost efficiency in mind.
- Contribute to platform automation efforts that simplify how teams build and deploy data pipelines.
- Build tooling, templates, or services that reduce manual effort and enable consistent engineering practices.
- Support adoption of standardized deployment, provisioning, and operational workflows across teams.
- Ensure data systems meet requirements for reliability, observability, data quality, and performance.
- Monitor and troubleshoot production pipelines, performing root cause analysis and implementing improvements.
- Contribute to CI/CD practices, testing strategies, and operational runbooks for data systems.
- Partner with Software Engineers, AI Engineers, and Data Scientists to deliver integrated, end-to-end solutions.
- Collaborate with platform, infrastructure, and governance teams to align on standards and shared capabilities.
- Contribute to technical discussions, design reviews, and architecture decisions within the team.
Benefits
- Retirement Plan
- 401k Matching
