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Recognizable consultancy brand, mid-level Data Engineer title, metro locations, and common experience band increase competition.
Data engineering skills are reasonably transferable, though Cloudera platform experience raises domain specificity.
Explicit 3–5 years plus mandatory Cloudera, Spark, CI/CD and SAST skills make filters strict.
Manage and optimize Cloudera CDP/CDH platforms including HDFS, Hive, Spark, YARN, Hue, and CDE ensuring high availability and platform health.
Build, deploy, and maintain CI/CD pipelines using Jenkins and GitHub/Bitbucket with integrated security and code quality tools like Checkmarx.
Develop and optimize PySpark and Python-based data processing solutions and write performant SQL queries for Hive and Impala environments.
3–5 years of relevant experience in data engineering and DevOps automation with Cloudera platforms.
Hands-on experience with Cloudera Hadoop/CDP platforms, Spark/PySpark, Python, Hive, YARN, Hue, and CDE.
Experience managing CI/CD pipelines with Jenkins, GitHub/Bitbucket and integrating SAST tools such as Checkmarx.
Strong Linux administration and scripting skills; knowledge of SQL and performance tuning.
Experienced in enterprise-scale data processing and platform administration focusing on Cloudera Hadoop ecosystems.
Proficient with DevOps practices particularly CI/CD pipeline construction and integration of security tools.
Capable of troubleshooting complex system issues and ensuring platform security, governance, and high availability.