Cloudera Data Engineer
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Key skills for this role
About the Role
Job Title Cloudera Data Engineer Job Scope We are seeking an experienced Cloudera Data Engineer with strong hands-on expertise in Cloudera CDP, Hadoop, Spark, Hive, and HDFS.
Key Skills for This Role
Full Job Posting
Job Scope
We are seeking an experienced
Cloudera Data Engineer
with strong hands-on expertise in
Cloudera CDP, Hadoop, Spark, Hive, and HDFS
.
The ideal candidate will be responsible for building and maintaining big data pipelines, optimizing data workflows, and supporting production environments to ensure reliability and performance.
Main Duties And Responsibilities
- Design, build, and maintain big data pipelines using Cloudera CDP components.
- Develop and optimize ETL/ELT workflows using Spark, Hive, and Hadoop ecosystems.
- Manage and maintain HDFS storage, ensuring high availability and performance.
- Perform production support activities, including issue resolution, monitoring, and performance tuning.
- Work with data scientists, analysts, and other engineering teams to support data-driven initiatives.
- Ensure data governance, security, and compliance across big data environments.
- Troubleshoot cluster-level issues related to resource utilization, scheduling, and configuration.
- Participate in solution design, architecture discussions, and technical documentation.
Position Requirements
- Strong hands-on experience with Cloudera CDP.
- Proficiency in Hadoop ecosystem: HDFS, YARN, MapReduce, Hive, Impala.
- Strong experience working with Apache Spark (PySpark or Scala preferred).
- Solid understanding of distributed systems and big data architecture.
- Experience with production support and troubleshooting in big data environments.
- Strong SQL skills and experience optimizing large-scale queries.
- Familiarity with Linux, shell scripting, and automation tools.
- Experience with version control (Git) and CI/CD workflows is a plus.
Education
Bachelor's degree in Computer Science or any other related field
Experience
- Experience with cloud platforms (AWS, Azure, GCP) for big data workloads.
- Exposure to Kafka, NiFi, Oozie, or similar data orchestration tools.
- Knowledge of Docker, Kubernetes, or containerized environments.
- Understanding of security, encryption, and data governance concepts.
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