Cloudera Data Engineer

About the role

An experienced Cloudera Data Engineer is sought to build and maintain big data pipelines, optimize data workflows and support production environments. The role covers Cloudera CDP, Hadoop, Spark, Hive and HDFS, with a focus on reliability and performance.

Key responsibilities

• Design, build and maintain big data pipelines using Cloudera CDP components.
• Develop and optimize ETL/ELT workflows using Spark, Hive and the Hadoop ecosystem.
• Manage and maintain HDFS storage, ensuring high availability and performance.
• Perform production support, including issue resolution, monitoring and performance tuning.
• Work with data scientists, analysts and other engineering teams on data-driven initiatives.
• Ensure data governance, security and compliance across big data environments.
• Troubleshoot cluster-level issues related to resource utilization, scheduling and configuration.
• Take part in solution design, architecture discussions and technical documentation.

Required profile

• Bachelor's degree in Computer Science or a related field.
• Strong hands-on experience with Cloudera CDP and the Hadoop ecosystem (HDFS, YARN, MapReduce, Hive, Impala).
• Solid understanding of distributed systems and big data architecture.
• Experience with production support and troubleshooting in big data environments.
• Experience with cloud platforms (AWS, Azure, GCP) for big data workloads; exposure to Kafka, NiFi, Oozie or similar orchestration tools; knowledge of Docker, Kubernetes or containerized environments.

Required skills

• Apache Spark (PySpark or Scala preferred)
• Strong SQL and optimization of large-scale queries
• Familiarity with Linux, shell scripting and automation tools
• Version control (Git) and CI/CD workflows are a plus