The Aircraft Operations Lab at UC3M (https://aircraftoperationslab.com/) is a research group at Universidad Carlos III de Madrid innovating for a safer, more resilient and sustainable aviation.
AI Methods (https://www.aimethods.com/) is a cutting-edge spin-off of the research group specializing in weather and aviation technologies. Our mission is to revolutionize the industry by leveraging artificial intelligence and data-driven approaches. We are committed to providing innovative solutions that enhance safety, efficiency, and decision-making in the field of weather and aviation.
Job Description:
As a Data Engineer at AI Methods, you will play a crucial role in developing and maintaining our data infrastructure. In addition to your regular responsibilities, we are thrilled to offer an internship opportunity that can be combined with your final bachelor’s or master’s thesis at the aircraft operations lab at Uc3M. This unique collaboration will allow you to work closely with both our team and the academic experts, bridging the gap between industry and academia.
Your responsibilities will include:
- Designing, implementing, and optimizing scalable data pipelines to handle large volumes of weather and aviation data.
- Integrating and processing diverse data sources, including weather APIs, satellite imagery, and aviation databases.
- Developing and maintaining data models and schemas to support advanced analytics and machine learning algorithms.
- Collaborating with cross-functional teams to understand data requirements and ensure data quality and integrity.
- Continuously monitoring and improving data pipelines for performance, scalability, and reliability.
- Leveraging your collaboration with the aerospace department at UC3M to incorporate relevant research and contribute to the advancement of weather and aviation technologies.
Qualifications:
- Bachelor’s or Master’s degree studies in Statistics, Computer Science, Data Science, Aerospace Engineering, or a related field at Carlos III University of Madrid.
- Proficiency in programming languages such as Python or Java.
- Strong knowledge of data modeling, ETL processes, and data warehousing concepts.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and related technologies (e.g., S3, Redshift, BigQuery).
- Familiarity with data visualization tools and techniques.
- Excellent problem-solving and analytical skills with a keen attention to detail.
- Strong communication and collaboration skills to work effectively in a team environment.
- It would be a big plus to have experience as a Data Engineer or similar role, preferably in the weather, aviation, or related domain.
Internship Details:
- Only candidates who are doing their bachelor’s or master’s degree final project in the UC3M are eligible for the internship.
- Successful candidates will have the chance to combine their thesis work with their role as a Data Analyst at AI Methods.
- This collaboration will provide valuable industry experience and access to cutting-edge weather and aviation technologies.
- The internship includes financial support during the thesis period.
Benefits:
- 15-20 hours per week.
- Salary of 400 to 550€ bruto.
- Opportunity to work with a dynamic and passionate team at the forefront of weather and aviation technologies.
- Opportunity to combine the internship with final bachelor or master thesis at UC3M.
- Flexible work hours and remote work options.
- Professional development opportunities to enhance your skills and knowledge.
- Exciting projects and the chance to make a significant impact in the industry.
How to Apply: To apply for the Data Engineer internship opportunity at AI Methods, please send your resume, a brief cover letter, and details about your ongoing or planned final thesis at the Aircraft Operations Lab UC3M to the email: masolera@ing.uc3m.es. We appreciate all applications, but only shortlisted candidates will be contacted for further steps.
AI Methods is an equal opportunity employer committed to diversity and inclusion. We encourage individuals from all backgrounds to apply.