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Tier-1 brand plus seniority and niche data-engineering skills produce moderate candidate density.
Specialized enterprise data platform work with finance and regulatory focus limits cross-industry portability.
Explicit 12+ years, principal seniority, and mandatory tech stack and governance requirements make screening highly strict.
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Lead architecture, design, and implementation of scalable enterprise data platforms for finance modernization.
Drive data platform modernization using Apache Spark, Apache Iceberg, AWS cloud services, and streaming technologies like Apache Kafka.
Establish enterprise-wide data engineering standards, reusable patterns, API development, and data governance frameworks.
12+ years of experience in data engineering, data platform development, or related technical roles.
Expert-level proficiency in Apache Spark (PySpark) and deep hands-on experience with Apache Iceberg or similar open table formats.
Experience designing and implementing streaming architectures using Apache Kafka and building REST APIs/microservices.
Work Experience Required: 12+ years; No explicit mention of educational degrees or location requirements.
Proven track record in architecting and delivering large-scale enterprise data platforms in a principal or lead capacity.
Strong expertise in modern data engineering tech stack (Spark, Iceberg, Kafka) combined with software engineering and DevOps practices.
Experienced in collaborating with finance leaders and cross-functional teams on finance modernization and regulatory data governance.