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Tier-1 brand, mid-level generalist data engineer with broad stack and metro hybrid location increases applicant competition.
Specialized big-data and streaming experience moderately limits cross-industry fit.
Explicit 4–8 years plus required Kafka, Spark, and language experience raises shortlisting strictness.
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Build and operate Kafka-based streaming applications for ingestion, filtering, enrichment, and replication at scale.
Develop and maintain data processing jobs using Apache Spark and/or Apache Flink adhering to platform standards.
Design and implement high-performance, scalable distributed systems supporting big data analytics and enterprise-grade applications.
4 to 8 years of experience in developing and maintaining enterprise-grade applications.
Proficiency in Java, Scala, Golang, or other modern programming languages.
Experience with Kafka for high-volume, scalable asynchronous task systems and microservices architectures.
Strong SQL skills with data modeling knowledge for analytical workloads.
Experienced in building and scaling complex distributed microservices and streaming systems in production environments.
Familiarity with big data processing frameworks, especially Apache Spark, Apache Flink, and query engines like Trino/Presto.
Comfortable working in cloud environments (AWS, OpenStack) and using container orchestration and management tools such as Kubernetes, Docker, and Helm.