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Mid-level big-data role in metro with popular title and broad skill requirements increases applicant competition.
Core big-data technologies (Spark, Kafka, Hadoop, NoSQL) are widely transferable across industries.
Multiple explicit years of experience and many mandatory big-data technologies make shortlisting strict.
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Own design, development, and support of a scalable, distributed SaaS-based Security Risk Prioritization platform processing billions of transactions daily.
Provide technical leadership in data platform architecture, technology roadmaps, and cross-functional solution delivery for Big Data and Micro-services environments.
Mentor engineering teams, lead innovation initiatives, and ensure high-quality architectural standards and performance benchmarking.
Bachelor’s degree in Computer Science or equivalent.
5+ years total professional experience, including significant Big Data engineering roles.
Proven experience with Java/Scala, Apache Spark, Kafka, Hadoop, RDBMS (Oracle or equivalent) and NoSQL (Cassandra or equivalent).
At least 2 years experience in Big Data architecture/design using Spark and 3+ years in Kafka, performance testing, and handling Big Data pipelines.
Experienced technical leader with hands-on expertise in scalable Big Data platform design and microservices architecture.
Demonstrated ability to lead cross-team projects, perform complex problem decomposition, and implement high-performance, compliant infrastructures.
Strong background in mentoring and guiding engineering teams, with deep knowledge of streaming, caching, search technologies (Solr/Elastic), and ML model deployment within Big Data ecosystems.