Description

Develop and maintain large-scale data processing solutions within the Hadoop ecosystem.

Responsibilities

• Design and implement data pipelines using the Hadoop stack and storage technologies.
• Develop ETL processes and manage data integration across distributed systems.
• Collaborate with architects and stakeholders to deliver business-critical applications.
• Execute code deployment and manage release processes within established team cadences.
• Evaluate new technologies to optimize distributed computing solutions.

Required Skills

• 9+ years of experience with the Hadoop stack (HDFS, MapReduce, YARN, Hive, Sqoop, Impala, Spark, Flume, Kafka, Oozie).
• Extensive knowledge of Big Data Enterprise architecture, preferably Cloudera.
• Hands-on experience with HBase, RDBMS, SQL, and ETL workflows.
• Proficiency in NoSQL technologies such as Cassandra or MongoDB.
• Strong Unix/Linux scripting skills and experience with AutoSys scheduling.
• Deep understanding of distributed computing principles and algorithms.
• Experience working within team delivery and release management processes.

Preferred Skills

• Python proficiency including Data Structures, Collections, Pandas, Django, and Flask.
• Experience with R, Tableau, and automated testing frameworks like JUnit.
• Knowledge of Kerberos for data security on the Hadoop ecosystem.

Any Big Data certification (ex. Cloudera's CCP, CCA) is a plus

Key Skills

Education

Any Big Data certification(ex. Cloudera's CCP, CCA) is a plus