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Remote, mid-level Data Engineer role with common Spark/Scala skills and metro appeal increases candidate competition.
Moderate industry transferability; core data engineering skills transferable but AdTech domain experience preferred.
Multiple mandatory tech filters (Spark, Scala, K8s, GCS) plus 5+ years requirement create strict shortlisting.
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Design, develop, and maintain scalable ETL pipelines and distributed data applications using Spark and Scala.
Optimize data workflows and platforms for batch and streaming workloads focusing on scalability, reliability, and cost-efficiency in cloud and containerized environments.
Collaborate with engineering, product, and analytics teams to deliver production-grade, high-performance data solutions and troubleshoot platform issues.
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).
Experienced in large-scale data platform development, especially in distributed data processing and batch/streaming data workflows.
Demonstrated ability to optimize and troubleshoot production data systems in cloud-native and containerized environments.
Comfortable working cross-functionally with engineering, product, and analytics teams in an AdTech or similar technology-driven environment.