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Remote, mid-level data engineer role with common title and metro context increases candidate competition.
Medium—core data engineering skills transfer broadly, but Scala/Spark and AdTech experience add domain specificity.
High due to explicit 5+ years requirement and mandatory Spark/Scala plus cloud and K8s experience.
Design, develop, and optimize scalable ETL pipelines and distributed data applications using Spark and Scala for large-scale data processing.
Collaborate with cross-functional teams to build reliable, production-grade data solutions for batch and streaming workloads.
Deploy and manage data workloads in cloud (Google Cloud Storage) and containerized environments (Kubernetes), troubleshoot production issues, and improve platform performance.
5+ years of experience in Data Engineering or Big Data Engineering.
Strong hands-on experience with Apache Spark and Scala.
Experience building and maintaining ETL pipelines.
Familiarity with Google Cloud Storage (GCS) and Kubernetes (K8s).
Professional with deep expertise in distributed data processing and large-scale data platform optimization.
Experienced in building production-grade, high-performance data pipelines in cloud and containerized environments.
Background or interest in AdTech systems and working with cross-functional engineering teams on scalable data solutions.