Mastercard is looking to unlock the full potential of its data assets by driving innovation, reducing friction in the management of big data assets, and ensuring seamless data accessibility across both public cloud and on-premise environments.
Requirements
- Extensive experience in cloud and data platform architecture, DevOps, or related roles, with proven leadership of cross-functional teams.
- Hands-on expertise with AWS and Azure services: S3, EC2, Lambda, Glue, Redshift, Lake Formation, Azure Data Factory, Fabric, Synapse, and Databricks.
- Strong track record of building DevOps pipelines and infrastructure-as-code using Terraform, CloudFormation, ARM templates, Azure DevOps, or GitLab CI/CD.
- Solid understanding of cloud security concepts, IAM design, data encryption, and governance frameworks.
- Experience with data engineering frameworks (Spark, PySpark) and large-scale ETL systems.
- Proficiency in scripting and automation using Python, Bash, or PowerShell.
- Demonstrated success delivering production-ready medallion architecture solutions.
Responsibilities
- Lead the design and delivery of end-to-end cloud-native solutions with a focus on Lakehouse architectures (S3, Azure Data Lake, Databricks, EMR, Athena, etc.).
- Drive CI/CD pipeline development, infrastructure-as-code, and automated environment provisioning across AWS and Azure.
- Set and enforce security best practices (IAM, encryption, network security) and ensure compliance with frameworks such as GDPR and HIPAA.
- Establish and enforce enterprise-grade data governance frameworks, including data cataloging, lineage, classification, and access control, leveraging tools like Lake Formation or Azure Purview.
- Design and lead implementation of robust data engineering pipelines, including ETL/ELT, data lakes, and data warehouses.
- Implement Lakehouse architectures using the medallion model (Bronze, Silver, Gold) with deep integration into AWS services (Glue, Lake Formation) and analytics engines (Databricks, EMR, Athena).
- Continuously monitor, troubleshoot, and optimize systems for performance, reliability, scalability, and cost efficiency.
Other
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Analytics, or a related field. Equivalent practical experience will also be considered.
- Strong problem-solving skills, with the ability to identify discordant views and engage in constructive dialogue to resolve them.
- Excellent verbal and written communication skills, with the ability to explain technical problems clearly and succinctly and effectively sharing vision and roadmaps with diverse stakeholders.
- Comfortable working in Agile/Scrum environments with strong collaboration skills.
- Ability to abide by Mastercard’s security policies and practices and ensure the confidentiality and integrity of the information being accessed.
