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Mid-level data engineer role, metro location, broad big-data skillset, and recognizable employer increase applicant competition.
Big-data engineering skills (Spark, Hadoop, Pyspark) transfer across industries but remain domain-specific.
Explicit 5+ years and mandatory big-data/CI-CD skills make screening and technical filtering stringent.
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Develop and maintain big data processing solutions using Hadoop, Hive, Spark, and PySpark.
Collaborate with cross-functional teams to gather requirements and deliver business-oriented solutions.
Implement and manage CI/CD pipelines using Jenkins to automate build, test, and deployment processes.
5+ years of software development experience.
Hands-on experience with Spark, PySpark, Hadoop, HDFS, and Hive.
Experience with CI/CD and DevOps tools including Jenkins, Maven, GIT, GitHub, and SonarQube.
Experience working with cloud platforms such as Azure or AWS.
Strong expertise in big data frameworks and tools, capable of handling data engineering tasks end-to-end.
Experienced working in Agile development environments with an understanding of DevOps practices.
Comfortable adapting to new technologies and troubleshooting production and development issues efficiently.