Description

You design and maintain distributed data systems using Hadoop and HPE MapR, owning batch and stream processing pipelines and cluster stability.

This role is hybrid.

Responsibilities

• Develop and optimize data engineering solutions on HPE MapR clusters.
• Build and maintain batch and stream processing workflows using Apache Spark.
• Manage Linux/Unix system administration tasks for cluster nodes.
• Write and refactor code in Python, Java, Scala, or Bash to support data pipelines.
• Collaborate with stakeholders to resolve complex data storage and computing challenges.

Required Skills

• 5+ years of Software Engineering or Data Engineering experience.
• 2–4 years of hands-on Hadoop experience, specifically with HPE MapR.
• Strong understanding of distributed systems and cluster computing.
• Proficiency in at least one programming language: Python, Java, Scala, or Bash.
• Working knowledge of Apache Spark for batch and stream processing.
• Linux/Unix system administration skills.

Preferred Skills

• Experience with data security and governance in Hadoop ecosystems.
• Familiarity with enterprise data platforms in financial services.

Key Skills

Education

Any Gradute