Senior ML Engineer

A leading South African renewable energy company that manages and operates utility-scale power plants is seeking a Senior Data & ML Engineer. In this pivotal role, you will set the technical direction and own the architecture for our enterprise data platform, driving innovation and reliability across our operations.

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 Single Source of Truth (SSOT) design to ensure consistency across business domains.
• Establish and enforce core engineering standards—including testing, CI/CD pipelines, and release protocols—via rigorous code reviews.
• Architect MLOps frameworks and machine learning 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, scalability, and seamless upgrade planning.
• Set fleetwide Asset Framework (AF) modeling, calculation, and mapping standards to drive 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 elevate team capabilities in emerging technologies.

Minimum Requirements

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field.
• Experience: 7 to 10 years of experience in data engineering or data platform development, with a minimum of 6 years demonstrating platform ownership at a Senior or 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: Demonstrated ability to influence executive leadership, align cross-functional teams, and mentor engineering talent.

Advantageous Skills

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

Benefits

• Competitive salary based on experience, with potential for upward adjustment depending on exceptional skills and qualifications.