As an Energy Data Portfolio Intern, you will work closely with the Energy Data Management team members, and focus on the French Renewable Scope, which includes a very large number of production sites (solar, hydro, and wind) to monitor.
Over the past years, the team has automated most of its processes using Python, PowerQuery, Power BI, Databricks and Alteryx. The operational tasks of the EDM team involve:
-
Collecting volumetric power data from multiple external and internal sources via APIs and retrieving any missing volumes.
-
Ensuring data consistency by comparing current data with historical records and other sources but also by building some coherence checks to identify anomalies.
-
Injecting validated data into the internal database and producing key performance indicators (KPIs) to ensure data quality.
Your primary responsibilities will include maintaining and executing these operational tasks, developing new controls to improve data reliability, and contributing to the issuance of Guarantees of Origin. Additionally, you will participate in the development of a Model Context Protocol (MCP) Server integrated with a Large Language Model (LLM).
This internship offers the opportunity to gain a deep understanding of the French energy market structure, collaborate with Front, Middle, and Back Office teams, and interact with external stakeholders such as RTE and Enedis. You will strengthen your programming expertise across multiple languages and actively support the migration to next-generation tools and platforms.
The team acts as the direct liaison to market system operators, ensuring continuous data collection from various sources. They are responsible for comparing volumes, performing controls and analysis, and cleaning the data. This enables seamless and flexible access to accurate and robust data, which is then shared with both internal and external stakeholders. The Energy Data Management team collaborates with relevant departments to ensure the accuracy of volumetric data when implementing it into the trading system and reviews the robustness of all internal systems related to this data.
