Data Analyst Intern — Ops Excellence

🚀 The role

Location: Paris — 7 rue Caumartin, 75009

Type: End-of-studies internship or gap year (SFE / césure)

Duration: 6 months

Start: ASAP

Bigblue is looking for a Data Analyst Intern to join the Ops Excellence team.

This is a hands-on engineering role at the core of our data infrastructure. You won't just work with data — you'll help build and maintain the pipelines, models, and systems that make data accessible and reliable for our entire Ops organization. This is a unique opportunity to contribute to production-grade data systems in a fast-moving logistics scale-up.

✍️ Our data challenges

• Data pipeline development: Design, build, and maintain ELT pipelines that ingest, transform, and consolidate raw warehouse and operational data into clean, analysis-ready datasets — using SQL, dbt, and BigQuery.
• Data modeling: Create and maintain data models that are well-structured, documented, and easy for analysts across Ops, Finance, and Product to use — applying best practices in schema design and data governance.
• Automation & tooling: Write robust, maintainable code that automates recurring data tasks, reduces manual work, and scales with our growing network of warehouses across Europe.
• Data quality & reliability: Monitor pipeline health, troubleshoot data issues, and take ownership of resolutions — so that the numbers our teams rely on are always accurate and up to date.
• Collaboration with Ops & Product: Work hand in hand with the Ops Excellence, Atlas (WMS), and Data teams to understand business needs and translate them into reliable data infrastructure.

🙌 Your profile

• Student in year 4 or 5 of an engineering school, computer science, or equivalent program
• Strong SQL skills — comfortable writing complex queries, optimizing for performance, and building data models from scratch
• Familiarity with data engineering tools and concepts: dbt, BigQuery, ELT pipelines, data warehousing
• Python or another scripting language is a strong plus
• You care about code quality, documentation, and long-term maintainability
• Rigorous and detail-oriented — you go deep to understand data before trusting it
• Comfortable working autonomously in a fast-paced, startup environment
• Fluency in English and French