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Metro location, mid-level experience range, broad Big Data+GCP skillset increases applicant competition.
Big Data and GCP skills transfer across industries but require specific platform experience.
Explicit 4–7 years plus mandatory Big Data and GCP tech stack narrow candidate pool.
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Design, develop, and maintain big data solutions using Core Java, Java 8, and Spring Boot.
Build and optimize big data pipelines leveraging Hadoop, Spark (Core & SQL), Hive, MapReduce, and PySpark.
Develop and manage data workflows and storage on Google Cloud Platform services including BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage (GCS).
4 to 7 years of relevant experience in big data engineering.
Strong programming skills in Core Java, Java 8, and Spring Boot.
Experience with big data technologies: Hadoop, Spark (Core & SQL), Hive, MapReduce, PySpark.
Proficiency with Google Cloud Platform big data services such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage (GCS).
Experienced working in the big data ecosystem combining Java development with cloud-native services on GCP.
Capable of managing end-to-end big data pipelines and workflows with performance optimization focus.
Able to integrate traditional big data frameworks with modern cloud-based data processing and storage solutions.