Senior Data Engineer H/F - CDI

About Primelis:

Primelis is an international martech group operating four flagship SaaS platforms: Market (marketplaces), Signal (competitive intelligence), Outrank (enterprise SEO), and BrandOS (brand governance). We work with premium global clients, including Stripe and Databricks, and generate 50% of our revenue in the United States.

To maintain visibility for every contribution and ensure a cohesive architecture, our data team is intentionally lean, consisting of 6 people (5 Engineers + 1 Head of Data).

Data is key… Over the coming years, we aim to scale rapidly, invest heavily in our technology, and strengthen our international footprint. To support this growth, we are looking for a Senior Data Engineer.

Your Missions:

• Pipeline Management: Design and maintain scalable data pipelines that power our 4 SaaS platforms.
• Stack Evolution: Upgrade and scale the modern data stack across ingestion, transformation, orchestration, and observability.
• Architecture & Tooling: Contribute directly to data architecture decisions and tooling choices, collaborating closely with the Head of Data and the CTPO.
• Code Excellence: Maintain a clean, tested, and reliable codebase to enable frictionless team growth.
• Impact: Drive high-impact improvements to our data stack by proposing new tools, processes, and methodologies.
• Data Contracts: Collaborate with product and software teams across all platforms to enforce robust data contracts.
• Core Algorithms: Contribute to the design of core product algorithms (bid optimization, keyword scoring, ranking signals).
• AI Integration: Embed AI agents (embedded Claude) into both development and analytics workflows.

Why Join Primelis?

• High-Growth Environment: A unique opportunity to join a fast-growing tech scale-up.
• Global Impact: Directly contribute to the business acceleration of premium global brands.
• Stimulating Domain: Work within an exciting e-commerce and marketplaces ecosystem.
• Lean & Visible: Join a tight-knit data team (6 people) where your impact is visible and the architecture remains consistent.
• Top-Tier Mentorship: Learn from a Head of Data with 15+ years of experience in data marketing, and a CTPO (Polytechnique alumnus) with a rigorous product and tech background.
• Modern Engineering Culture: Native engineering standards (testing, CI/CD, IaC, AI agents).
• Career Growth: Access international career opportunities.
• Team Spirit: Work in an inclusive environment with an ultra-motivated team.

Profile Requirements:

• Experience: 3 to 5 years of experience in Data Engineering (or Software Engineering with a strong focus on data).
• Core Tech: Proficiency in SQL and Python; hands-on experience with GCP or AWS, and BigQuery or Snowflake.
• Modern Data Stack: Proven experience running a modern data stack in production, including integration and transformation tools (dbt).
• Engineering Depth: Deep understanding of core data engineering topics: CI/CD, scheduling, monitoring/alerting, cloud data processing services, Docker, data lakes, and data warehouses.
• Architecture: Ability to formulate data architecture recommendations and experience deploying new tech/frameworks.
• Infrastructure: Knowledge of Terraform (IaC) is highly appreciated.
• Bonus: Experience with AI agents or LLMs in a production environment is a significant plus.

Technical Stack:

• Languages: SQL, Python
• Cloud & Storage: GCP, BigQuery, Cloud Run
• Transformation & Ingestion: dbt, custom ELT
• DevOps & Infra: CI/CD (GitLab CI), Docker, Cloud Run, Terraform (IaC)
• Orchestration: Cloud Scheduler
• Observability: Data monitoring, alerting, and observability tools
• AI: AI Agents (Claude embedded in development workflows)

Interview Process

1. Discovery Call (Video - 30 min): An introductory chat with Marine (Talent Acquisition) to get to know each other and discuss your career goals.
2. Technical Deep Dive (Video - 45 min): A technical interview with Benjamin (Head of Data).
3. Final Deep Dive (Video - 45 min): A technical and strategic interview with Clément (CTPO).