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Tier-1 brand, popular Data Engineer title, metro location, and broad required skills increase candidate competition significantly.
Core data platform skills transfer across industries but payments/regulatory and large-scale multi-tenant experience increase domain specificity.
Principal-level, enterprise-scale platform experience, specific distributed processing and governance requirements create strict hiring filters.
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Lead architecture and modernization of Mastercard's Rewards Data Platform supporting 400+ customers and millions of daily transactions.
Define enterprise data engineering strategy including workflow orchestration, data integration, and scalable distributed data processing solutions.
Provide hands-on technical leadership, mentorship, and set engineering standards across multiple teams and programs.
Proven experience as Principal Data Engineer, Lead Data Engineer, or Data Architect in enterprise-scale environments.
Expertise in workflow orchestration, distributed data processing, data lakes/lakehouse architectures, data modeling, and database design.
Strong experience with Apache Spark, Databricks, Hadoop, Kafka/streaming platforms, relational and NoSQL databases, and cloud platforms (Azure, AWS, or GCP).
Work Experience Required: Not explicitly mentioned in the JD.
Senior technical leader experienced in designing and operating mission-critical, scalable, and secure multi-tenant data platforms.
Strong influencer capable of shaping engineering standards and architectural frameworks across organizations in complex environments.
Background in financial services, payments, or loyalty platforms with experience in cloud migration and data platform modernization.