Data & ML Engineer Cape Town

Hire Resolve is actively recruiting for a Data & ML Engineer position in Cape Town. This is an excellent opportunity for professionals in the Ict / Computer sector looking to advance their careers.

• Experience Level: 5 - 7 years • Educational Background: Bachelor or equivalent • Industry Focus: Ict / Computer • Location Preference: in Cape Town

ICT professionals in Data & ML Engineer positions drive digital innovation. This role is crucial for businesses undergoing digital transformation in South Africa.

This role in Ict / Computer offers valuable career progression opportunities aligned with your experience level and professional aspirations.

When applying for this Data & ML Engineer position, ensure your CV highlights: • Relevant experience matching the 5 - 7 years requirement • Educational qualifications in line with Bachelor • Specific achievements in the Ict / Computer field • Any certifications or specialized training

The Ict / Computer sector in South Africa continues to show strong demand for skilled professionals. This position represents a valuable opportunity in the current job market.

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Salary: R51 333.00 - R68 500.00 Per Month Job Type: Permanent Sectors: IT Reference: 204847 Job Type: Permanent Sectors: IT Reference: 204847 Sectors: IT Reference: 204847 Reference: 204847

Employer: Hire Resolve

A leading independent power producer (IPP) focused on developing, owning, and operating clean and reliable electricity generation across Africa is seeking a Data & ML Engineer who will drive the technical implementation of the company's Data Transformation initiative.

Ingestion & Orchestration: Design and maintain modular pipelines (API, SQL, ETL/ELT) integrating sources like CAMs, ERP, OT/IoT, and SharePoint into the SSOT. Data Modeling: Develop robust schemas and feature pipelines supporting analytics, reporting, and ML. Operational Health: Manage domain monitoring, alerting, incident resolution, advanced SQL performance tuning, and schema design. Model Development: Build, evaluate, and fine-tune ML models (forecasting, anomaly detection, neural networks) using standard libraries, actively managing overfitting and drift. Pipeline Integration: Embed feature engineering and model scoring into automated data workflows. MLOps Delivery: Implement end-to-end MLOps for domain use cases, including versioning, CI/CD, deployment, monitoring, and automated retraining. Configuration: Own AVEVA PI and CAMs for the domain; design PI Asset Framework (AF) element templates, hierarchies, and internal calculations. Lifecycle Management: Oversee asset onboarding/offboarding, ensuring accurate data registration, configuration, and alignment with reporting frameworks. Integrations & Alerts: Configure notifications, event frames, and PI interfaces to maintain high data integrity across SSOT integrations. End-to-End Delivery: Function as single-point-of-contact for domain data products, making scalable architecture decisions and filling technical gaps independently. Standards & Compliance: Enforce data governance, security, IT standards, and structured change management (approvals, rollback plans). Collaboration & Mentorship: Translate complex technical concepts for non-technical stakeholders, coordinate cross-divisional timelines, review associate work, and mentor team members on emerging practices.

Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field. Experience: 5–7 years in data engineering or data platform development (5+ years acceptable with strong evidence of independent delivery ownership). Technical Experience: Practical hands-on ownership of API integration, ETL/ELT orchestration, data modeling, and production operations. Tooling: Strong SQL and Python skills, ETL/automation frameworks, and experience integrating ML models into production workflows. Programming & Querying: Strong Python and advanced SQL (schema design, indexing, performance tuning). C# is an advantage. Data Architecture: Proven track record designing scalable ingestion frameworks, integrations, and enterprise data models. ML & MLOps: Solid theoretical ML foundations combined with practical production deployment and MLOps practices. Industrial Platforms: Hands-on experience configuring AVEVA PI (Asset Framework, interfaces, event frames) and CAM platforms. Soft Skills: High autonomy, technical discipline, cross-functional communication, and stakeholder management. AdvantageousAVEVA PI: Hands-on integration via PI Integrator or PI Web API / SDKs. Advanced ML: Production deep learning exposure (e.g., TensorFlow, PyTorch) and MLOps tooling. Big Data & Orchestration: Experience with Data Lakes, Azure Data Factory, Airflow, or Prefect. Domain & Low-Code: Energy/industrial IoT experience, plus familiarity with Power Apps and Power Automate. Benefits:Competitive salary based on experience (salary can potentially be more based on experience/skills)IF you meet the above requirements and want to make a career-changing move, apply today by emailing your CV to [Email hidden - Login to reveal]