Energy data analyst - £35,000 - London
| Posting date: | 12 August 2025 |
|---|---|
| Salary: | £25,000 to £35,000 per year |
| Hours: | Full time |
| Closing date: | 11 September 2025 |
| Location: | Central London, London, sw1w 0ex |
| Company: | Pertemps |
| Job type: | Contract |
| Job reference: | 57552477 |
Summary
Energy data analyst - £35,000 - London
Job Summary:
We are seeking a highly analytical and detail-oriented Data Energy Analyst to join our team. The ideal candidate will be responsible for collecting, analysing, and interpreting energy consumption data to support strategic decision-making, sustainability goals, and cost-reduction initiatives. This role requires strong data analysis skills, knowledge of energy systems and markets, and the ability to present insights to technical and non-technical stakeholders.
Key Responsibilities:
- Collect, process, and analyse energy usage data from multiple sources (e.g., utility bills, meters, BMS/EMS systems).
- Monitor and evaluate energy performance trends across facilities, assets, or portfolios.
- Identify inefficiencies, anomalies, and opportunities for energy savings or operational improvements.
- Develop dashboards, reports, and visualizations to communicate findings to stakeholders.
- Support energy forecasting, budgeting, and procurement strategies.
- Collaborate with engineering, operations, and sustainability teams on energy projects and initiatives.
- Ensure compliance with energy regulations and reporting requirements (e.g., ENERGY STAR, ISO 50001, ESG frameworks).
- Stay informed about energy market trends, technologies, and best practices.
Qualifications:
- Bachelor’s degree in engineering, Environmental Science, Data Science, Statistics, Economics, or a related field.
Experience:
- 2–5 years of experience in energy analysis, data analytics, or sustainability-related roles.
- Familiarity with energy systems (HVAC, lighting, renewables, etc.) is preferred.
Technical Skills:
- Proficiency in data analysis tools (e.g., Excel, SQL, Python, R, Power BI, Tableau).
- Experience with energy management systems, utility data platforms, or smart meter data.
- Understanding of statistical modelling, regression analysis, or forecasting techniques.
Job Summary:
We are seeking a highly analytical and detail-oriented Data Energy Analyst to join our team. The ideal candidate will be responsible for collecting, analysing, and interpreting energy consumption data to support strategic decision-making, sustainability goals, and cost-reduction initiatives. This role requires strong data analysis skills, knowledge of energy systems and markets, and the ability to present insights to technical and non-technical stakeholders.
Key Responsibilities:
- Collect, process, and analyse energy usage data from multiple sources (e.g., utility bills, meters, BMS/EMS systems).
- Monitor and evaluate energy performance trends across facilities, assets, or portfolios.
- Identify inefficiencies, anomalies, and opportunities for energy savings or operational improvements.
- Develop dashboards, reports, and visualizations to communicate findings to stakeholders.
- Support energy forecasting, budgeting, and procurement strategies.
- Collaborate with engineering, operations, and sustainability teams on energy projects and initiatives.
- Ensure compliance with energy regulations and reporting requirements (e.g., ENERGY STAR, ISO 50001, ESG frameworks).
- Stay informed about energy market trends, technologies, and best practices.
Qualifications:
- Bachelor’s degree in engineering, Environmental Science, Data Science, Statistics, Economics, or a related field.
Experience:
- 2–5 years of experience in energy analysis, data analytics, or sustainability-related roles.
- Familiarity with energy systems (HVAC, lighting, renewables, etc.) is preferred.
Technical Skills:
- Proficiency in data analysis tools (e.g., Excel, SQL, Python, R, Power BI, Tableau).
- Experience with energy management systems, utility data platforms, or smart meter data.
- Understanding of statistical modelling, regression analysis, or forecasting techniques.