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Tier-1 brand, metro location, and mid-level generalist data role drive high candidate competition.
Core data engineering skills transfer well, but financial services governance increases domain specificity.
Explicit 5+ years and required Spark, Kafka, Airflow, AWS, and governance experience imply stringent filters.
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Lead design, development, and troubleshooting of scalable platform services governing open source acquisition, usage, and compliance.
Build and operate batch and streaming data pipelines using Spark, Kafka, and Airflow with focus on reliability, observability, and performance optimization on AWS cloud.
Define data integration patterns, operational runbooks, and drive engineering best practices for stable production support and compliance telemetry.
5+ years of applied software engineering experience with formal training or certification.
Proficiency in building production services with languages relevant to Spark, Kafka, Airflow, cloud-native architecture, including strong data engineering skills.
Practical experience with CI/CD automation, operational stability, and secure coding practices within the Software Development Life Cycle.
Experience designing and building scalable data pipelines implementing Medallion Architecture layers for compliance telemetry on AWS cloud.
Experienced in engineering cloud-native distributed data systems, particularly using Apache Spark and AWS services, with focus on scalability and security governance.
Familiar with financial services IT requirements including traceability, control alignment, and audit-ready evidence.
Skilled at translating compliance and open source governance metrics into operational dashboards and actionable insights for engineering and governance stakeholders.