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Mid-level metro role at a known employer with niche Spark/Databricks skills — moderate competition.
Domain-specific data platform skills transferable across industries but require platform experience.
Explicit 3–4 years plus mandatory Databricks, Spark, Kafka skills enforce strict filters.
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Develop and maintain scalable batch and streaming data pipelines using Apache Spark and Apache Flink.
Manage and optimize Databricks environments including workspaces, clusters, jobs, and workflows to ensure performance and cost efficiency.
Configure, deploy, and troubleshoot Kafka and Kafka Connect for event-driven data processing and support platform reliability through monitoring and incident response.
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
3–4 years of experience in software engineering or data engineering.
Strong programming skills in Java, Scala, or Python with hands-on experience in Apache Spark and Databricks environment management.
Practical knowledge of Apache Flink, Apache Kafka including Kafka Connect, Git, and CI/CD practices.
Experienced in building and operating enterprise-scale data platforms with expertise in batch and streaming data pipelines.
Skilled in managing cloud-native data engineering tools with a focus on platform automation, performance optimization, and cost management.
Able to collaborate cross-functionally with engineering teams to deliver reliable, observable, and scalable data solutions in a production environment.