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Mid-level (3-5 yrs) data engineer with common big-data stack yields moderate competition.
Requires specific Hadoop/Cloudera/Spark expertise, so background transferability is limited.
Explicit 3-5 year requirement plus mandatory Hadoop, Spark, Cloudera, and Kafka skills increases selection strictness.
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Design, implement, and maintain scalable data ingestion and transformation workflows within a Cloudera Hadoop environment.
Develop and optimize Spark-based jobs and orchestration workflows, ensuring reliability and adherence to development standards.
Collaborate with cross-functional teams using agile methodology to translate business requirements into technical solutions and manage incident resolution.
3-5 years of experience in Big Data Engineering or similar roles.
Proficiency with Hadoop & Cloudera ecosystem including Yarn, Kafka, HDFS, Iceberg.
Strong development skills in Spark and PySpark.
Knowledge of Azure Big Data systems and cloud computing.
Experienced in operating within agile teams contributing to fast-paced, business-oriented development with timely delivery focus.
Able to manage incident procedures rigorously and mentor peers ensuring high code quality and standards adherence.
Comfortable working under pressure with strong collaboration skills across business and technical stakeholders.