Intern – Data Analyst – 2026
Pubblicato il 20-10-2026 - Baker Hughes in Firenze
Would you like the opportunity to work in a global energy company?
Do you enjoy taking on challenging projects?
Join our innovating Internship Program
The Baker Hughes Internship is designed to enable students either pursuing a Bachelors’ or Masters’ degree or recently graduated to gain hands-on work experience as the foundation of their professional lives. Our internships will give you first-hand insights into the processes, systems, and practices that are aligned to ensure customer needs are met through flawless execution and the application of leading-edge technology.
Partner with the best
You’ll participate in focused training, and team meetings, work on projects, and present your results. During your internship, you will be supported by a buddy and your manager who will ensure you have a valuable learning experience. You can expect to receive coaching and mentoring to enable you to complete assignments and projects to develop your learning and skillset.
You will also have the opportunity to become familiar with the Health, Safety, and Environment (HS&E;)
and culture of Baker Hughes. as well as our strong commitment to diversity, equity and inclusion.
The Data Analyst Intern support the Aeroderivative Engines team in data analysis and process improvement activities. The intern will assist in managing internal databases, developing tools, and preparing reports that support the full project lifecycle—from early tendering phases to final customer delivery.
This internship offers the opportunity to work in a technical and international environment, building strong analytical and organizational skills within the aeroderivative engines domain.
As a Data Analyst Intern, you will be responsible for:
• Support the update and maintenance of the GTE Aero Engines database.
• Contribute to the creation of standard reports and dashboards for project support.
• Collaborate in the improvement of processes and data‑driven tools used by the team.
• Analyze large datasets, t