• Build the data foundations for AI agents. AI agents are becoming the main way people query data. You'll help design the next generation of our warehouse and data models so that agents can understand them, trust them and answer questions correctly: clear semantics, well-documented metrics and structures built for machines as much as for humans.
• Expand our data coverage to sensitive domains. Finance and HR data are joining our scope. You'll help bring them into the warehouse with the right level of rigor, access control and confidentiality.
• Strengthen the existing data domains. Marketing, Sales and Product Analytics already rely on us. We want to make their data more complete, reliable and easy to use, on Snowflake today and ClickHouse soon.
• Make data part of everyone's daily work. Our goal is for every team at GitGuardian to use Data & AI tools every day. That depends on trustworthy data models and clearly defined business metrics.
• Keep the platform running smoothly while it grows. Day-to-day data requests and run topics matter. Handling them well lets the whole squad keep delivering on the larger projects of a 12–18 month roadmap.

• Write data models as code daily (SQL, Python with Snowpark and PySpark) to deliver new data for business insights.
• Own your topics end to end, from ingestion to consumption by business users.
• Work with internal stakeholders (Sales, Marketing, Finance, HR, Product) to understand their needs and turn them into well-defined business metrics.
• Build and orchestrate pipelines with Dagster, and deploy them with Docker and Terraform on AWS.
• Take part in the run: monitor pipelines, investigate data issues, and answer data requests from across the company.
• Keep the code base healthy through code reviews, tests and documentation.
• Work closely with the squad's AI Engineers so that our data powers the company's internal AI tools.

Technical environment

• Coding Languages: Python (Snowpark & PySpark), SQL
• Analytics databases: Snowflake, ClickHouse
• Visualisation: Metabase
• Orchestration: Dagster
• Deployment: Docker, Terraform
• Cloud Provider: AWS
• VCS: GitLab
• CI/CD: ArgoCD

If you think you match at least 70% of these criteria, please apply!

• A first experience in data engineering, such as an internship, apprenticeship or up to about 2 years in a role.
• Strong SQL and good Python skills.
• An understanding of data modeling concepts (dimensional modeling, fact and dimension tables, business metrics).
• The ability to find your way in an existing, complex code base and learn from it quickly.
• Comfort talking with non-technical stakeholders, asking the right questions and explaining your choices.
• A high standard for quality: you care about data that is correct, tested and documented.
• Fluent English in an international environment.
• Availability to work from our office 3 days a week.

• Experience with Snowflake and/or Clickhouse
• Familiarity with agentic systems or LLM-based architectures applied to data pipelines.
• Experience in high-growth startups or scale-ups.

The interview process

At GitGuardian, we are committed to building a diverse, equitable and inclusive workforce.

We will ask for your gender identity on the application page to help us understand the diversity of our applicant pool and to track our progress in attracting and hiring a diverse workforce. The information is optional and will not be disclosed to the hiring manager or the interview team and will not be considered in the hiring process. We appreciate your willingness to share this with us so that we can continue to improve our diversity, equity and inclusion efforts.

1. Manager interview

To discover your professional project and evaluate if there could be a mutual match

2. Technical interview with the team (1h30)

Purpose: We validate your hard skills and give you the opportunity to discuss with other staff engineers and data engineers

Skills Assessed: Python coding proficiency, Data architecture skills and overall communication and reasoning.

3. Engineering leadership interview

Purpose: To know more about yourself and your achievements, and present to you the team.

Skills Assessed: We assess your soft skills (ownership, communication) and motivation.

4.1 Final interview with Eric our CEO, onsite

Purpose: To detail our company’s vision and ambitions for the next couple of years.

You will also meet some team members for a coffee.

4.2 References check

You can start thinking about two contacts who can attest to your previous or current professional experiences. These contacts should be as recent as possible, and we will call them at the end of the process.