Data & ML Engineer

Job Summary

A company that develops, owns, and operates utility-scale power generation and energy storage plants across the African continent is seeking a Data & ML Engineer who will execute the technical implementation of the company's initiative under the direction of the Data Engineering Manager.

Key Responsibilities

• Pipeline Design: Build and maintain modular, reusable ingestion and orchestration (APIs, SQL stored procedures, ETL/ELT) connecting sources such as CAMs, ERP, OT/IoT, and SharePoint into the SSOT.
• Modeling & Optimization: Design coherent data models and feature pipelines supporting analytics and ML; execute advanced SQL performance and index tuning.
• Operations: Maintain domain operational health, including active monitoring, alerting, performance tuning, and incident resolution.
• Model Development: Build, evaluate, and integrate ML algorithms (forecasting, anomaly detection, neural networks) into active data workflows using standard Python libraries.
• MLOps Implementation: Manage data/model versioning, CI/CD, drift monitoring, overfitting controls, and automated retraining pipelines for owned use cases.
• Platform Configuration: Own AVEVA PI and CAMs for assigned sites/domains, designing Asset Framework (AF) element templates, hierarchies, event frames, and notifications.
• Lifecycle Management: Oversee asset onboarding/offboarding, ensuring proper registration, interface maintenance, and data alignment with SSOT dashboards.
• Standards & Security: Enforce data governance, IT security standards, and structured change management (approvals and rollback procedures).
• Architectural Decisions: Autonomously make scalable design choices for owned domains, seeking alignment on major structural decisions.
• Communication: Translate complex technical decisions and trade-offs for non-technical business stakeholders.
• Mentorship & Delivery: Review peer code, mentor associates, drive cross-divisional alignment to meet timelines, and introduce new ML/data capabilities to the team.

Requirements

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related quantitative field.
• Experience: 5–7 years in data engineering or platform development (5+ years acceptable with a demonstrated track record of independent delivery ownership).
• Technical Experience: Hands-on experience with API integrations, ETL/ELT orchestration, data modeling, production operations, and deploying ML models.
• Skills & Competencies
  • Programming & Querying: Strong Python and advanced SQL (schema design, index tuning, performance optimization). C# is an advantage.
  • Data & ML Engineering: Proven ability to build end-to-end ingestion frameworks, data models, and feature pipelines alongside solid MLOps discipline.
  • Industrial Platforms: Practical experience managing AVEVA PI (AF modeling, interfaces, event frames) and CAMs.
  • Core Behaviors: High degree of self-direction, strong engineering discipline, and clear stakeholder communication skills.
• Advantageous
  • OT / Industrial Integration: Direct configuration of AVEVA PI tools (e.g., PI Integrator, APIs) and hands-on experience with energy/industrial IoT data.
  • Advanced ML: Production experience with MLOps frameworks and deep learning libraries (TensorFlow, PyTorch).
  • Cloud & Big Data: Experience with data lake architectures and orchestration tools (Azure Data Factory, Airflow, or Prefect).
  • Low-Code Automation: Working knowledge of Power Apps and Power Automate.

Remuneration & 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 itcareers@hireresolve.za.com