Senior Data & ML Engineer

Job Description

• A South African company that manages and operates utility-scale renewable energy power plants across South Africa is seeking a Senior Data & ML Engineer who will set the technical direction and own the architecture for the company's enterprise data platform.

Responsibilities:

• Design robust ingestion, orchestration, and integration architectures across ERP, OT/IoT, CAMs, and SharePoint systems, optimizing for scale, cost, resilience, and security.
• Own the enterprise data model and SSOT design to ensure consistency across business domains.
• Establish and enforce core engineering standards (testing, CI/CD pipelines, release, and rollback protocols) via rigorous code reviews.
• Architect MLOps frameworks and ML data pipelines, defining standard patterns for algorithm development and library usage.
• Design integration patterns to power ML models using operational (AVEVA PI) and asset management data.
• Define and govern standards for the responsible adoption of AI and Generative AI tools.
• Own the technical architecture for AVEVA PI and CAMs, ensuring high availability, scaling, and seamless upgrade planning.
• Set fleetwide Asset Framework (AF) modeling, calculation, and mapping standards, driving analytics-led alerting and cross-site data integrity.
• Resolve complex, cross-system architectural challenges and lead major incident reviews.
• Enforce enterprise data governance, security, and model risk standards.
• Align cross-divisional stakeholders and leadership on strategic technical decisions.
• Mentor engineers, cultivate a culture of technical excellence, and drive team capability in emerging technologies.

Minimum Requirements:

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field.
• Experience: 7–10 years in data engineering or data platform development (minimum 6 years with demonstrated platform ownership at a Senior/Lead level).
• Technical Mastery: Advanced SQL and Python skills, hands-on experience with ETL/ELT, enterprise data modeling, and scalable MLOps.
• Track Record: Proven experience leading platform architecture, enforcing engineering standards, and managing complex production environments.
• Data Engineering & Architecture: Expert-level SQL, ETL/ELT pipelines, data modeling, and platform-wide architectural design.
• ML & AI Infrastructure: Advanced capability in MLOps, production ML integration, and AI readiness.
• OT & Asset Systems: In-depth technical mastery of AVEVA PI, Asset Framework (AF) modeling, and CAMs integration.
• Reliability & Governance: Strong focus on operational discipline, system availability, and risk management.
• Leadership: Proven ability to influence executive leadership, align cross-functional teams, and mentor junior engineers.

Advantageous

• Enterprise-level AVEVA PI architecture (HA, upgrades, AF modeling) in industrial/energy sectors.
• Production ML frameworks (e.g., PyTorch, TensorFlow) and orchestration tools (e.g., Azure Data Factory, Airflow, Prefect).
• Cloud data lake/big data architectures and formal AI/ML governance frameworks.