Lead Data Engineer (Data Platforms)
Core
Design, build, and scale cloud-based data and analytics solutions within Mastercard's Data Commercialization Platform, focusing on BI, data engineering, and platform capabilities.
Role type
Lead Data Engineer (Data Platforms)
Builds
Cloud-native data and BI solutions, scalable data pipelines, and analytics frameworks on multi-cloud environments.
Domain
Financial services / Cloud Data Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Cloud-native architecture design, Databricks (AWS/Azure), Snowflake, AWS services (S3, Glue, EMR), CI/CD pipelines, Infrastructure as Code, distributed systems, scalable architectures, technical leadership, mentorship
Preferred skills
Azure Databricks, ADLS Gen2, AKS, open data formats (Delta Lake, Apache Iceberg), data governance frameworks, multi-cloud interoperability, FinOps, platform observability
Technologies
Databricks, Snowflake, AWS, Azure, S3, Glue, EMR, IAM, ADLS Gen2, AKS
Responsibilities
Design and develop cloud-native data and BI solutions; Build scalable, high-performance data pipelines and analytics frameworks; Enable seamless integration across Databricks, Snowflake, AWS, and Azure services; Build and maintain CI/CD pipelines, automation frameworks, and infrastructure-as-code; Implement secure and governed access patterns including RBAC and service principals; Support data platform interoperability across multiple compute engines and cloud providers
Seniority
Senior, hands-on IC with leadership responsibilities