O&M Analytics Engineer - Cape Town

O&M Analytics Engineer - Cape Town

Application Deadline: 14 May 2025

Department: Operations & Maintenance

Employment Type: Permanent - Full Time

Location: South Africa

Description

For more than 20 years, Globeleq has been a long-term investor, developer, owner and operator of diversified power projects in Africa, where the company is one of the largest Independent Power Producers., With nearly 1500MW of generation capacity in operation across 16 power plants in 7 countries, 488MW of new power projects in construction and >2,000MW in development, Globeleq is one of the largest independent power producers solely focused in Africa. Globeleq is 70% owned by British International Investment and 30% by Norfund, the development finance institutions of the UK and Norway, and has a proven track record for supporting the ongoing development of the African power sector.   
 
Globeleq’s various generation technologies include gas, wind, solar PV, battery energy storage (BESS), and geothermal. The company is also actively pursuing new opportunities which are emerging from the energy transition, including desalination projects powered by renewables, as well as green hydrogen and ammonia projects. 

In this role, the O&M Analytics Engineer is responsible for data analysis and performance management of the Globeleq assets, leveraging advanced data analytics to optimise operations, minimise downtime, and maximise energy output. This role will also involve providing critical support to our Remote Operations Centre (ROC) and on-site teams, focusing on SCADA/DCS systems, maintenance management, and the integration of new power plants.

The O&M Data Analytics Engineer will form part of our technical shared services team, contributing to the development of digital management systems, O&M projects, integration of new power plants, and the ongoing improvement of our operations.

Key Responsibilities

Responsible for the development, maintenance and management of data management and acquisition systems:

• Utilise IoT integration tools to connect and configure all on-site assets, ensuring seamless data flow and integrity within the organisation's industrial data management system (IDMS)
• IDMS maintenance, continued functionality, component/asset on-boarding (integration)
• Assist the Data Analytics Manager in the development/automation of centralised data management and storage systems, monitoring and reporting within the Business Intelligence department 
• Develop asset monitoring and management features
• Provide business support on DCS/SCADA and other I&C systems on the power plants
• Support the implementation of O&M systems into the ERP
• Develop and improve data automation systems to support performance management and compliance reporting
• Identify and understand SCADA, data collection and automation systems used on the assets to support integration to 3rd party systems

Support Operations, and Maintenance (O&M) functions to minimise downtime and expenditure:

• Asset performance management: Monitor asset data availability and provide under performance insights, performance trends and insights to drive business decisions
• Trigger investigations based on performance reports and support Root Cause Analysis (RCA)
• Develop performance and event identification analyses in the IDMS
• Tracking high-priority maintenance projects and developing the reporting systems to communicate it to the business
• Investigate asset performance, event identification, maintenance/inspection triggers and escalating identified issues to ROC
• Execute cross-functional projects or maintenance activities
• Investigate feasibility and contribute to improvement projects
• Develop and improve monitoring screens for ease of monitoring and event identification
• Drive initiatives to support sites in maintaining and improving operations through equipment and data availability audits

Perform other work-related activities as delegated by the Data Analytics Manager.

Skills, Knowledge and Expertise

Skills and Competencies:

• Programming: Proficiency in programming languages such as Python, R, SQL, and C++
• SQL and Data Architecture: Expertise in designing and implementing scalable data architectures, with proficiency in data modelling
• Algorithm Development: Experience in developing algorithms to solve complex analytics problems, using programming languages such as Python, R, MATLAB, SQL
• Machine Learning: Knowledge of machine learning techniques, including supervised and unsupervised learning, neural networks, and deep learning
• Data Analysis and Visualisation: Familiarity with data visualization tools and techniques, with ability to communicate complex data insights effectively
• Proven competency in troubleshooting and analysing data, including following various types of process charts, schematics, single line diagrams
• Able to manage stress and high-pressure situations
• High learning proficiency
• Able to handle multiple projects, prioritise work and work effectively under limited supervision – extreme ownership
• Excellent verbal and written communication; includes being responsive, having good listening skills and being able to communicate appropriately with all levels of personnel
• Good team player; able to balance team and individual responsibilities

Experience, Knowledge and Qualifications:
Minimum requirements:

• BEng in Mechanical Engineering, Electrical Engineering, Computer Science, or related fields
• Three years’ work experience in the renewable energy industry with a high focus on solar PV and wind energy. In particular, experience in renewable energy power plant operations or field, maintenance is preferred
• High proficiency in the SQL, data science, Industrial data management systems/data historians and performance analysis systems, python and Microsoft Office packages
• Proven competency in troubleshooting and analysing data
• Knowledge of industrial network data communications, client/server functions and hardware/software architectures
• Experience in industrial management systems, including Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Human-Machine Interface (HMI) software 
• Code B driver’s license

Advantageous:

• Certification in data science, machine learning, or related fields
• Experience with ERP/CMMS systems, such as SAP or IFS
• Experience in working with the AVEVA PI system or similar portfolio data historian and performance analysis systems