Description

Design and implement scalable data solutions within the Hadoop ecosystem to support business-critical applications.

This role is on-site.

Responsibilities

• Build and maintain data pipelines using the Hadoop stack and distributed computing principles.
• Develop ETL processes and manage data integration across RDBMS, SQL, and NoSQL environments.
• Execute code deployment and release processes following established team cadences.
• Evaluate new technologies to innovate and deliver scalable big data solutions.
• Collaborate with architects and stakeholders to deliver technical requirements.

Required Skills

• 8+ 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.
• Proficiency with NoSQL technologies such as Cassandra or MongoDB.
• Experience with HBase, RDBMS, and SQL.
• Strong Unix/Linux scripting skills and experience with Autosys scheduling.
• Deep understanding of distributed computing principles.
• Strong analytical capabilities and interest in algorithms.

Preferred Skills

• Python proficiency including Data Structures, Collections, Pandas, Django, or Flask.
• Experience with R, Tableau, or automated testing frameworks like JUnit.
• Knowledge of data security on Hadoop using Kerberos and Big Data certifications such as Cloudera CCP or CCA.

Key Skills

Education

Not Required