Design, build, deploy, and maintain scalable batch, streaming, and real-time data pipelines supporting business-critical products and analytics workloads.
Develop reusable frameworks and services for data ingestion, transformation, orchestration, and data delivery across multiple platforms and environments.
Build and support enterprise data lake, warehouse, and lakehouse solutions that enable large-scale data processing and analytics.
Lead initiatives focused on platform scalability, performance optimization, reliability, resiliency, and operational efficiency.
Implement and enhance data quality, observability, governance, security, lineage, and monitoring capabilities across data ecosystems.
Partner with product, engineering, analytics, and business teams to understand data requirements and deliver solutions that drive measurable business outcomes.
Support modernization and cloud migration initiatives, helping evolve legacy platforms to modern cloud-native architectures.
Enable advanced analytics, reporting, AI/ML, experimentation, and customer insights use cases through robust and trusted data foundations.
Establish engineering best practices, development standards, CI/CD automation, infrastructure-as-code, and data platform operational excellence.
Troubleshoot complex production issues and lead root-cause analysis efforts to improve platform stability and service reliability.
Mentor engineers and contribute technical leadership across multiple initiatives, promoting innovation, knowledge sharing, and engineering excellence.
Drive continuous improvement through automation, simplification, and adoption of modern data engineering practices and technologies.
Contribute to architectural decisions and technology roadmaps that shape the future of Mastercard’s Marketing Services data platforms.