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# Statistical Review Data Lead

- **Company:** Energy Institute
- **Location:** UK
- **Experience:** Expert
- **Salary:** £38,000.0
- **Contract:** Temporary contract
- **Skills:** Microsoft Access, Microsoft Excel, Business Analytics Applications, Data Analysis, Big Data, Databases, Data Validation, Data Visualization, Database Development, Pivot Tables, Power BI, Standard Sql, SQL Databases, Data Processing, Web Content, Powerquery, Core Data, Vba Programming Language, Data Management, Data Delivery
- **Published:** October 16, 2026
- **Apply:** https://www.totaljobs.com/job/data-lead/energy-institute-job108185034

## About the Role

We are looking for a highly analytical and detail-oriented data professional with a passion for energy data and the energy transition. The ideal candidate will combine strong technical and data management skills with excellent project coordination and stakeholder engagement abilities. They will be comfortable working with large, complex datasets, managing multiple deadlines, and communicating technical information clearly to a range of audiences. Most importantly, they will be committed to accuracy, quality, collaboration, and continuous improvement in delivering one of the world's most respected energy datasets., * 2-5 years' experience in a data analysis, research, statistical review or related role.

 * Strong technical skills in Microsoft Access, Excel, VBA and SQL, including database management, automation, Power Query, pivot tables and handling large datasets.
 * Strong analytical and data validation skills, with the ability to investigate anomalies, reconcile data sources, apply consistent methodologies and produce accurate outputs.
 * Good understanding of global energy markets, energy transition trends and energy accounting principles and metrics.
 * Experience with Power BI, R or other data visualisation and analytical tools to support reporting, dashboards and repeatable analyses would be advantageous.
 * Strong project management and organisational skills, with the ability to coordinate contributors, manage competing priorities and deliver to deadline.
 * Excellent communication, stakeholder management and team leadership skills, with the ability to explain complex information to technical and non-technical audiences.
 * Collaborative, detail-oriented and committed to maintaining high standards of accuracy, consistency and transparency in published data.

Desirable

 * Additional language skills, particularly Chinese and/or Arabic, would be beneficial.

## Description

This is an exciting opportunity to join one of the most globally recognised and high-profile energy statistics projects. You would have hands-on experience in helping to manage some of the key stakeholder relationships as well as improve the methodology, reporting and systems level of the global statistical review. This is a hybrid role and would require you to be in the London office two days a week. Your tasks would include:

 * Lead the end-to-end delivery of the Statistical Review of World Energy dataset, covering data processing, database management, validation, quality assurance and final publication of data outputs.
 * Oversee and coordinate the data processing and validation work of an external analyst team, including KPMG and Kearney, and academic research partners covering onboarding, progress monitoring and data delivery management to meet tight deadlines.
 * Own core data management processes, including maintaining the Statistical Review database, running queries, building validation checks and producing final outputs used for analysis, publishing and digital products.
 * Act as a key point of contact for data-related queries, providing clear explanations of methodology, definitions, data limitations and year-on-year changes.
 * Provide support for database development, optimisation and transformation initiatives, collaborating closely with internal database engineering to test and validate calculation formulas, conversion factors, and data models across relational SQL environments.
 * Conduct thorough data reconciliation and quality reviews across historical time-series and analytical datasets, ensuring calculation formulas, conversion factors, and regional aggregations maintain complete methodology consistency.
 * Develop robust quality control processes to identify inconsistencies, reconcile source data, document assumptions and ensure outputs are accurate, transparentand publication ready.
 * Provide analytical support for wider Energy Institute content using Statistical Review data, including the Country Transition Tracker, regional insights, stakeholder briefings and presentations, and web-based data products.
 * Build practical analytical tools, templates and calculators that help EI colleagues interpret, interrogate and communicate Statistical Review data more effectively.
 * Create engaging charts, tables and graphics that translate complex energy data into accessible outputs for reports, presentations, web content and stakeholder communications.