Senior Data Engineer: Oracle Cloud Data & ML Pipelines

BICRM; Pretoria; On-site; ZAR 1,200,000 - 1,800,000; Part time

Job summary

Our Johannesburg Office at BICRM is hiring top Data Engineers with Oracle Finance Cloud migration experience on an 18 months renewable contract. You are a senior data engineer with 10+ years of data engineering experience and a track record in data modelling, pipelines, and cloud–on‑premise integration.

Responsibilities include designing and managing data pipelines, building cloud-based analytics infrastructure, and deploying ML models, with strong DevOps/DataOps credentials and ML framework

Qualifications

• Senior data engineer with Oracle Finance Cloud migration experience.
• 10+ years data engineering experience.
• Experience designing and managing data pipelines.
• Experience with cloud and on-premise data infrastructure.

Responsibilities

• Conduct data modelling on transactional and BI data assets to inform data architecture.
• Design, create and manage data pipelines.
• Develop, implement and review data-related architecture, infrastructure, processes, and procedures.
• Develop infrastructure to support hybrid data and analytics projects, integrating cloud and on-premise services.
• Implement cloud-based data analytics infrastructure.
• Demonstrate understanding of machine learning concepts.
• Show experience with DevOps and/or DataOps.
• Work with ML frameworks and libraries; deploy and maintain ML models.

Skills

Data modelling

Data pipelines

Hybrid data integration

Cloud data analytics

DevOps/DataOps

ML concepts

ML frameworks

ML model deployment

Oracle Finance Cloud migration

Tools

Oracle Finance Cloud

Job description

Our Johannesburg Office at BICRM is hiring top Data Engineers with Oracle Finance Cloud migration experience on an 18 months renewable contract. You are a senior data engineer with 10+ years of data engineering experience and a track record in data modelling, pipelines, and cloud–on‑premise integration.

Responsibilities include designing and managing data pipelines, building cloud-based analytics infrastructure, and deploying ML models, with strong DevOps/DataOps credentials and ML framework