MA

Mastercard · mastercard.wd1.myworkdayjobs.com · checked today

Principal Data Engineer (Data Platforms)

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.

Skills, with evidence

• Data modelling
  Strong foundations in modern data architectures such as lakehouse and medallion, data lifecycle management, data modeling, database design, distributed systems, and performance optimization.must havewrong?
• Data quality
  Build governance, privacy, quality, lineage, cataloging, retention, and access management into the platform by design.must havewrong?
• Python
  We are looking for a hands-on, passionate engineer and architect with strong PySpark, Python, cloud and modern data-architecture expertise.must havewrong?
• Spark
  Design processing and query architectures using Databricks, Snowflake, Spark, and Trino, with open table and file formats such as Iceberg, Delta Lake, and Parquet.must havewrong?
• Streaming
  Experience designing batch, streaming, API, and secure data-sharing architectures and integrating heterogeneous systems across cloud environments.must havewrong?
• AWS
  Design AWS data-platform architecture using S3, IAM, EKS, networking, and relevant cloud-native data services, and Azure architecture using ADLS, Microsoft Entra ID, Azure RBAC, Key Vault, AKS, and relevant analytics services.must have · not practised herewrong?
• Java
  Experience designing distributed control-plane applications using Java and/or Python, REST and gRPC APIs, asynchronous messaging, workflow and state management, authentication and authorization, multi-tenancy, idempotency, resiliency, auditability, and operational observability.must have · not practised herewrong?
• Kubernetes
  Design Kubernetes platforms for portable compute, workload isolation, security, scaling, observability, and deployment across cloud, private, sovereign, and on-premises environments.must have · not practised herewrong?
• Airflow / orchestration
  Own and optimize infrastructure for data storage, processing, orchestration, networking, identity, secrets, security, reliability, and cost.wrong?
• Cost & performance
  evaluate federation, replication, and compute-to-data using latency, cost, regulation, residency, freshness, reliability, and operational complexity.wrong?
• Warehousing
  This role will design scalable distributed and lakehouse platforms across regions and execution environments;wrong?
• Governance & security
  establish federated governance, metadata, access, and query patterns;not practised herewrong?
• Azure
  Design AWS data-platform architecture using S3, IAM, EKS, networking, and relevant cloud-native data services, and Azure architecture using ADLS, Microsoft Entra ID, Azure RBAC, Key Vault, AKS, and relevant analytics services.not practised herewrong?
• SQL
  Design processing and query architectures using Databricks, Snowflake, Spark, and Trino, with open table and file formats such as Iceberg, Delta Lake, and Parquet.wrong?