Rackspace Technology - San Antonio, TX

posted 15 days ago

Full-time - Senior
Remote - San Antonio, TX
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

The Senior Big Data Hadoop ML Engineer at Rackspace is a remote position focused on developing scalable batch processing systems using the Apache Hadoop ecosystem. The role requires extensive experience in machine learning pipelines and strong programming skills in Java and Python. The engineer will leverage Google Cloud Platform (GCP) for big data processing and storage, while implementing automation and DevOps best practices.

Responsibilities

  • Develop scalable and robust code for large scale batch processing systems using Hadoop, Oozie, Pig, Hive, Map Reduce, Spark (Java), Python, Hbase
  • Develop, manage, and maintain batch pipelines supporting Machine Learning workloads
  • Leverage GCP for scalable big data processing and storage solutions
  • Implement automation/DevOps best practices for CI/CD, IaC, etc.

Requirements

  • Proficiency in the Hadoop ecosystem with Map Reduce, Oozie, Hive, Pig, HBase, Storm
  • Strong programming skills with Java, Python, and Spark
  • Knowledge in public cloud services, particularly in GCP
  • Experienced in Infrastructure and Applied DevOps principles in daily work
  • Ability to tackle complex challenges and devise effective solutions
  • Proven experience in engineering batch processing systems at scale
  • Hands-on experience in public cloud platforms, particularly GCP
  • 10+ years of experience in customer-facing software/technology or consulting
  • 5+ years of experience with 'on-premises to cloud' migrations or IT transformations
  • Technical degree: Computer Science, Software Engineering or related

Nice-to-haves

  • Familiarity with Terraform
  • Familiarity with Python
  • 5+ years of experience building, and operating solutions built on GCP

Benefits

  • Variable compensation in the form of bonus, commissions, or other discretionary payments based on performance
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