Role Overview
As a Director, Data Engineering within the Data Collection & Engineering (DC&E) organisation, you will lead strategic data engineering initiatives that enable Mastercard's enterprise data ecosystem. You will be responsible for defining and executing the technology vision for large-scale Data Warehouse, Data Lakehouse, and Data Platform solutions supporting advanced analytics, AI, product innovation, regulatory reporting, and operational intelligence.
About Mastercard
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.
Key Responsibilities
- Define and execute the long-term Data Engineering strategy aligned with Mastercard's AI, analytics, digital payments, and data platform roadmap
- Lead the architecture and implementation of highly scalable, secure, and resilient Data Lakehouse and Data Warehouse platforms
- Lead large-scale migration programmes moving enterprise data workloads from legacy platforms to cloud-native architectures
- Build, lead, and develop high-performing teams comprising Managers, Principal Engineers, Lead Engineers, and Senior Data Engineers
- Oversee delivery of multiple strategic programmes supporting Mastercard's analytics, data science, product development, fraud, and regulatory functions
Requirements & Eligibility
- 15+ years of experience delivering enterprise-scale Data Warehouse, Data Lake, Lakehouse, and Big Data solutions
- 7+ years of leadership experience managing engineering managers, architects, and distributed engineering teams
- Deep expertise designing and implementing large-scale data platforms using Apache Kafka, Apache Spark, Scala/Java/Python, Hadoop ecosystem technologies, and Distributed storage and compute architectures
- Extensive experience designing cloud-native architectures on AWS and hybrid cloud environments
Required Skills & Tech
Apache KafkaApache SparkScalaJavaPythonHadoopAWSAmazon S3EMRGlueAthenaEKSAirflowNiFiOracleSQL ServerCassandra