Lead design and delivery of cloud BI/analytics platform solutions using Databricks, Snowflake, AWS and Azure. Drive multi-cloud interoperability, governance, automation, security controls, and platform roadmaps to enable governed self-service analytics at scale.
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
Principal Data Engineer
Role Summary
Join the Data Commercialization Platform (DCP) engineering team to design and build cloud-based architectures for Business Intelligence and analytics, leveraging Databricks and Snowflake on AWS, with multi-cloud extension patterns into Azure. You will lead platform-grade solutions that are governed, scalable, and interoperable, using open data standards and enterprise security controls.
What You'll Do (Key Responsibilities)• Design and develop cloud BI/analytics architecture on AWS Databricks and Snowflake, enabling governed analytics, ML, and data engineering workloads at scale. • Drive multi-cloud architecture patterns by extending DCP capabilities into Azure, including Azure Databricks (ADB) and ADLS Gen2, while maintaining an engine-agnostic posture. • Lead cross-platform interoperability across Databricks, Snowflake, and AWS data services (e.g., catalog federation and governed access patterns), ensuring seamless end-user experiences and consistent security controls• Participate in architecture reviews, iteration planning, and feature sizing with technical partners across Mastercard, shaping platform roadmaps and execution plans.• Define and deliver service-level procedures and platform solutions (automation, provisioning, repeatability), improving reliability, speed-to-onboard, and operational excellence. • Build roadmaps and identify improvement opportunities for primary platform services (cost optimization, governance, automation, resiliency, multi-region strategy.• Introduce new technologies and architectures aligned with enterprise standards, emphasizing open formats (Iceberg/Delta) and avoiding vendor lock-in. • Own requirements management and project planning/control for platform initiatives, including delivery coordination and operational readiness. • Enable secure access and automation patterns (service principals, role-based controls, separation of duties) across Databricks, Snowflake, and AWS. • Support BI enablement on Databricks, including approved capabilities like Databricks AI/BI, driving governed self-service analytics adoption.
Core Platform & Technology Scope (Must-Have Exposure)• Databricks (AWS + Azure Databricks) - analytics/ML, lakehouse patterns, governed catalogs and platform enablement. • Snowflake - distribution/consumption platform patterns and multi-platform coexistence with Databricks. • AWS - platform services supporting analytics and governance (e.g., data lake + orchestration + compute patterns). • Azure - DCP multi-cloud extension patterns (ADB + ADLS Gen2) for regulated/client-driven needs.
Required Qualifications• Proven experience designing cloud analytics / BI architectures for large-scale data platforms. • Hands-on expertise across Databricks + Snowflake + AWS, with demonstrated ability to integrate governed services across platforms. • Working knowledge of Azure architectures and patterns for extending analytics platforms (including Azure Databricks and ADLS Gen2). • Strong architecture and engineering leadership: ability to drive standards, automation, and repeatable delivery• Experience operating in enterprise governance/security constraints, implementing access control and automation identities (service principals).
Preferred Qualifications (Nice to Have)• Familiarity with open table formats and interoperability patterns (e.g., Iceberg/Delta) in multi-engine environments. • Experience building or operating platform automation (workspace provisioning, access automation, CI/CD enablement)
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
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
Principal Data Engineer
Role Summary
Join the Data Commercialization Platform (DCP) engineering team to design and build cloud-based architectures for Business Intelligence and analytics, leveraging Databricks and Snowflake on AWS, with multi-cloud extension patterns into Azure. You will lead platform-grade solutions that are governed, scalable, and interoperable, using open data standards and enterprise security controls.
What You'll Do (Key Responsibilities)• Design and develop cloud BI/analytics architecture on AWS Databricks and Snowflake, enabling governed analytics, ML, and data engineering workloads at scale. • Drive multi-cloud architecture patterns by extending DCP capabilities into Azure, including Azure Databricks (ADB) and ADLS Gen2, while maintaining an engine-agnostic posture. • Lead cross-platform interoperability across Databricks, Snowflake, and AWS data services (e.g., catalog federation and governed access patterns), ensuring seamless end-user experiences and consistent security controls• Participate in architecture reviews, iteration planning, and feature sizing with technical partners across Mastercard, shaping platform roadmaps and execution plans.• Define and deliver service-level procedures and platform solutions (automation, provisioning, repeatability), improving reliability, speed-to-onboard, and operational excellence. • Build roadmaps and identify improvement opportunities for primary platform services (cost optimization, governance, automation, resiliency, multi-region strategy.• Introduce new technologies and architectures aligned with enterprise standards, emphasizing open formats (Iceberg/Delta) and avoiding vendor lock-in. • Own requirements management and project planning/control for platform initiatives, including delivery coordination and operational readiness. • Enable secure access and automation patterns (service principals, role-based controls, separation of duties) across Databricks, Snowflake, and AWS. • Support BI enablement on Databricks, including approved capabilities like Databricks AI/BI, driving governed self-service analytics adoption.
Core Platform & Technology Scope (Must-Have Exposure)• Databricks (AWS + Azure Databricks) - analytics/ML, lakehouse patterns, governed catalogs and platform enablement. • Snowflake - distribution/consumption platform patterns and multi-platform coexistence with Databricks. • AWS - platform services supporting analytics and governance (e.g., data lake + orchestration + compute patterns). • Azure - DCP multi-cloud extension patterns (ADB + ADLS Gen2) for regulated/client-driven needs.
Required Qualifications• Proven experience designing cloud analytics / BI architectures for large-scale data platforms. • Hands-on expertise across Databricks + Snowflake + AWS, with demonstrated ability to integrate governed services across platforms. • Working knowledge of Azure architectures and patterns for extending analytics platforms (including Azure Databricks and ADLS Gen2). • Strong architecture and engineering leadership: ability to drive standards, automation, and repeatable delivery• Experience operating in enterprise governance/security constraints, implementing access control and automation identities (service principals).
Preferred Qualifications (Nice to Have)• Familiarity with open table formats and interoperability patterns (e.g., Iceberg/Delta) in multi-engine environments. • Experience building or operating platform automation (workspace provisioning, access automation, CI/CD enablement)
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard's security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
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