Gen AI Data Engineer Intern - Barcelona (Hybrid)

Fossil; Barcelona; Hybrid; EUR 8,900 - 13,000; Part time

Benefits offered by this job

Gen AI internship

Mentorship

Global analytics team

Barcelona office

Job summary

Fossil is seeking a data-focused intern in Barcelona to help build Gen AI pipelines, vector search, and AI-driven analytics within our global Data and Analytics team. The role is a 12-month internship, hybrid, based in Barcelona with onsite Monday-Thursday and remote on Fridays.

You will gain hands-on experience preparing structured and unstructured data, explore Retrieval-Augmented Generation architectures, support data governance, and collaborate with senior data scientists and AI/ML engineers

Qualifications

• Graduate student in CS/Math/IS/Engineering required.
• Advanced SQL and relational/dimensional DB design experience.
• Familiarity with enterprise data management and ETL/ELT concepts.
• Strong problem-solving, self-direction, and accountability.
• Excellent written and verbal English communication.

Responsibilities

• Assist Gen AI pipeline development including RAG architectures and embeddings workflows.
• Support data exploration, dataset curation, and database modeling.
• Assist integration of data sources and vector processing in a global enterprise context.
• Contribute to data governance, privacy, cataloging, and responsible AI practices.
• Collaborate with senior data scientists and AI/ML engineers in agile delivery.

Skills

SQL proficiency

Data governance mindset

Problem solving

English communication

Education

Master’s or PhD in CS/Math/IS/Engineering

Tools

Python

Linux shell scripting

SQL databases

ETL vs ELT concepts

Job description

Fossil is seeking a data-focused intern in Barcelona to help build Gen AI pipelines, vector search, and AI-driven analytics within our global Data and Analytics team. The role is a 12-month internship, hybrid, based in Barcelona with onsite Monday-Thursday and remote on Fridays.

You will gain hands-on experience preparing structured and unstructured data, explore Retrieval-Augmented Generation architectures, support data governance, and collaborate with senior data scientists and AI/ML engineers