Linux Data Engineer at Discovery Limited

Key Purpose

• Provide continuous monitoring and support of Linux environments. Design and implement containerized solutions for machine learning models. Technical leadership and ownership of Linux environments .

Areas of responsibility may include but not limited to

• Administration & continuous monitoring of Linux environments
• Optimize machine learning models & solutions produced by Data Scientists & Actuaries
• Participate in the architecture of ML environments and frameworks
• Provide ongoing support and enhancement to ML models
• Estimate time and resource requirements for business requirement
• Container management and automation
• Implement Redhat/Linux best practice and standards
• Conduct root cause analysis on production issues
• Technical leadership of entire information management process of both structured and unstructured data
• Implementing machine learning algorithms in production through integration
• Configuration of the Big Data infrastructure and environment for optimal performance
• Work closely with Data Scientists & Actuaries in productionisation of ML model
• Producing relevant technical documentation and specifications
• Develop data processing functions (DPF’s) using Java or Python, etc.

Education and Experience

• Matric (Essential)
• Minimum 3 – 5 years’ experience
• Redhat certification (Advantageous)
• National Diploma in IT (BTech) or appropriate certification (Advantageous)
• Bachelor of Science (Information Systems, Computer Science, Mathematics) Advantageous
• Linux administration (Intermediate)
• Linux Shell Scripting (Intermediate)
• Distributed programming skills on a cluster environment (Intermediate)
• Container setup (e.g., Docker) (Intermediate)
• Python/R/Scala Programming (Intermediate)
• Git versioning
• Spark Configuration (Intermediate)
• CI/CD
• Systems Development Life Cycle (SDLC) (Intermediate)
• Data Security and Protection Policies (Intermediate)
• Big Data using Hadoop (Intermediate)
• SQL (Basic)
• Java/.net Programming (Advantageous)
• Big Data Ingestion using Sqoop/Kafka (Advantageous)
• MS Excel (Basic)