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Data Engineer Intern (Gen AI & Analytics) – Temporary 12 Months

Fossil S.L., Calle Casp 21, Barcelona, Barcelona, Spain

Live, first seen by us 14 days ago
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Employment
Temporary — employment source
Make an Impact Are you passionate about data engineering and eager to build real-world Generative AI applications? Join our dynamic global Data and Analytics team in Barcelona for an exciting internship where you will work on cutting-edge data pipelines, vector search, and AI-driven analytics to empower enterprise innovation. This is a temporary (12-month contract), hybrid internship position based in our Barcelona office. You will be required to work onsite from Monday through Thursday, with the flexibility to work remotely on Fridays. What you will do in this role: Gen AI & LLM Pipeline Development Gain hands-on experience preparing structured and unstructured data to build modern Gen AI pipelines, including Retrieval-Augmented Generation (RAG) architectures and embedding ingestion workflows.
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Before you apply

New graduates
For current studentsEducation: Currently enrolled in a graduate program (Master s or PhD) in Computer Science, Mathematics, Information Systems, Engineering, or a related discipline

What you’ll work on

Full posting
  • Prepare structured and unstructured data for RAG and embedding pipelines

  • Support data integration and vector processing workflows

  • Explore data, curate prompt context datasets and model databases

  • Help connect to internal and external data sources and administer databases

  • Support data governance, privacy, cataloging and data hygiene efforts

From the employer’s posting
preparing structured and unstructured data to build modern Gen AI pipelines, including Retrieval-Augmented Generation (RAG) architectures and embedding ingestion workflows
Support data integration and vector processing workflows across our global enterprise ecosystem.
Perform data exploration, analysis, prompt context dataset curation, database modeling, and stewardship activities
Assist senior engineers in connecting to internal and external data sources, database administration
Support data governance initiatives by helping establish guidelines for data privacy, cataloging, classification, and responsible AI practices.
Education & alternatives
Who You Are Must-Haves: Education: Currently enrolled in a graduate program (Master’s or PhD) in Computer Science, Mathematics, Information Systems, Engineering, or a related discipline. Database & SQL Expertise: Advanced SQL capabilities alongside solid expertise in relational and dimensional database design.
Apply at Fossil Group

Posting record

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Status in our records
Live
First seen by us
Oct 20, 202614 days ago
Recorded sightings
24
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 14

Similar jobs usually come down between day 6 and day 54.

From 10,764 similar postings that came down. Coming down is not always a hire.

Fossil Group is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Shell
  • SQL
  • BigQuery
  • MySQL
  • Power BI
  • Snowflake
  • Spark
  • Tableau
Where the posting names them
Preferred & Nice-to-Haves: Programming & Automation: Strong programming proficiency in Python (or equivalent) along with shell scripting expertise in Linux environments. Gen AI Tools: Experience or familiarity with vector databases (e.g., Pinecone, Chroma, Vertex AI Vector Search), LLM orchestration frameworks (e.g., LangChain, LlamaIndex), and RAG/embedding workflows.
Education: Currently enrolled in a graduate program (Master’s or PhD) in Computer Science, Mathematics, Information Systems, Engineering, or a related discipline. Database & SQL Expertise: Advanced SQL capabilities alongside solid expertise in relational and dimensional database design. Data Management Principles: Familiarity with enterprise data management practices, ingestion methodologies, and foundational knowledge of ETL versus ELT frameworks.
Gen AI Tools: Experience or familiarity with vector databases (e.g., Pinecone, Chroma, Vertex AI Vector Search), LLM orchestration frameworks (e.g., LangChain, LlamaIndex), and RAG/embedding workflows. Data Platforms & APIs: Practical experience with modern analytical databases (e.g., BigQuery, Dataproc, Snowflake, PrestoDB, MySQL, Spark), BI tools (Tableau, Power BI), and API-driven integrations (Postman, MOVEit, WS FTP). CDP & Marketing Tech: Exposure to CDPs (e.g., Segment, Amperity) or ESP platforms (e.g., Bloomreach) is a distinct advantage.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Make an Impact Are you passionate about data engineering and eager to build real-world Generative AI applications? Join our dynamic global Data and Analytics team in Barcelona for an exciting internship where you will work on cutting-edge data pipelines, vector search, and AI-driven analytics to empower enterprise innovation. This is a temporary (12-month contract), hybrid internship position based in our Barcelona office. You will be required to work onsite from Monday through Thursday, with the flexibility to work remotely on Fridays. What you will do in this role: Gen AI & LLM Pipeline Development Gain hands-on experience preparing structured and unstructured data to build modern Gen AI pipelines, including Retrieval-Augmented Generation (RAG) architectures and embedding ingestion workflows. Perform data exploration, analysis, prompt context dataset curation, database modeling, and stewardship activities to support automated task execution. Engineering & System Integration Assist senior engineers in connecting to internal and external data sources, database administration, and applying software development lifecycle best practices. Support data integration and vector processing workflows across our global enterprise ecosystem. Data Governance & Quality Support data governance initiatives by helping establish guidelines for data privacy, cataloging, classification, and responsible AI practices. Ensure data hygiene and alignment with enterprise security frameworks. Cross-Functional Collaboration Collaborate closely with senior data scientists, AI/ML engineers, and global business stakeholders to learn and implement industry best practices. Participate in Agile/Waterfall product delivery iterations to build scalable analytics and AI solutions. Who You Are Must-Haves: Education: Currently enrolled in a graduate program (Master’s or PhD) in Computer Science, Mathematics, Information Systems, Engineering, or a related discipline. Database & SQL Expertise: Advanced SQL capabilities alongside solid expertise in relational and dimensional database design. Data Management Principles: Familiarity with enterprise data management practices, ingestion methodologies, and foundational knowledge of ETL versus ELT frameworks. Problem-Solving & Mindset: Strong problem-solving mindset with demonstrated self-direction, high accountability, and strong task management skills. Languages: Exceptional written and verbal communication capabilities in English. Preferred & Nice-to-Haves: Programming & Automation: Strong programming proficiency in Python (or equivalent) along with shell scripting expertise in Linux environments. Gen AI Tools: Experience or familiarity with vector databases (e.g., Pinecone, Chroma, Vertex AI Vector Search), LLM orchestration frameworks (e.g., LangChain, LlamaIndex), and RAG/embedding workflows. Data Platforms & APIs: Practical experience with modern analytical databases (e.g., BigQuery, Dataproc, Snowflake, PrestoDB, MySQL, Spark), BI tools (Tableau, Power BI), and API-driven integrations (Postman, MOVEit, WS FTP). CDP & Marketing Tech: Exposure to CDPs (e.g., Segment, Amperity) or ESP platforms (e.g., Bloomreach) is a distinct advantage. What We Offer A hands-on, high-impact internship working with cutting-edge Gen AI and enterprise data technologies Direct mentorship and collaboration with senior global data engineering and AI/ML leaders A collaborative, dynamic, and international working environment in Barcelona Professional growth and skill development within a global analytics organization  
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Fossil S.L., Calle Casp 21, Barcelona, Barcelona, Spain

Make an Impact Are you passionate about data engineering and eager to build real-world Generative AI applications? Join our dynamic global Data and Analytics team in Barcelona for an exciting internship where you will work on cutting-edge data pipelines, vector search, and AI-driven analytics to empower enterprise innovation. This is a temporary (12-month contract), hybrid internship position based in our Barcelona office. You will be required to work onsite from Monday through Thursday, with the flexibility to work remotely on Fridays. What you will do in this role: Gen AI & LLM Pipeline Development Gain hands-on experience preparing structured and unstructured data to build modern Gen AI pipelines, including Retrieval-Augmented Generation (RAG) architectures and embedding ingestion workflows.
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