About the position
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.
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.
Minimum 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.
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 Address Removed].com
Desired Skills:
- Data & ML Engineer
- Data & ML Engineer
- Data & ML Engineer
