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Metro locations, popular Data Engineer title, and broad Java/GCP/Big Data skillset increase competition.
Data engineering skills transfer across industries but require specific Big Data and GCP experience.
Explicit 6–9 years plus mandatory Java, Big Data, and GCP skills make filters strict.
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Design, develop, and maintain scalable ETL/ELT and data processing pipelines using Java-based big data frameworks on Google Cloud Platform.
Build and optimize batch and streaming data solutions leveraging GCP services such as Dataproc, Dataflow, BigQuery, and Pub/Sub.
Collaborate with cross-functional teams, perform code reviews, and mentor junior engineers while ensuring high-quality, maintainable code and cost/performance efficient architectures.
6 to 9 years of hands-on experience in data engineering or related software development roles.
Strong expertise in Java programming including OOP, data structures, collections, concurrency, and Java IO.
Proven experience with Big Data technologies such as Apache Spark (Java/Scala APIs), Hadoop, Hive, and SQL.
Hands-on experience with Google Cloud Platform services like BigQuery, Cloud Storage, with preferred exposure to Dataflow, Dataproc, and Pub/Sub.
Experienced in designing and implementing scalable, fault-tolerant distributed data processing systems using Java and Big Data frameworks on cloud platforms, especially GCP.
Comfortable working across batch and streaming data pipelines with a good grasp of cloud-native data architectures and cost optimization.
Experienced in collaborative agile environments involving code reviews, sprint planning, and mentoring, indicating mid to senior-level operating style.