Staff Data Engineer

About GitGuardianGitGuardian is a global cybersecurity scale-up. The company is based in Paris, New York City, Boston.Our early investors include Scott Chacon, co-founder of GitHub, and Solomon Hykes, co-founder of Docker, alongside leading US and European VC firms. We raised our Series C in early 2026.GitGuardian leads the way in securing the credential layer, helping organizations protect the secrets that let code, machines, and AI agents access systems with broad detection, identity context, and remediation at scale. Already trusted by 600K+ developers worldwide and by 50 of the Fortune 500!About your team and your missionYou will join the Public Intelligence team, whose mission is to leverage public data to detect exposed secrets, map them to the correct company, assess their severity, and enable timely and relevant alerts for customers and prospects.

The team works on ingesting public data (notably from GitHub and other sources), identifying the owning organization behind exposed secrets, analyzing the impact of these exposures, and evolving current systems toward more agentic and real-time architectures.The existing systems are mature and battle-tested. We are now at a pivotal moment: the goal is to redesign the end-to-end architecture to make it more robust, scalable, and aligned with significantly larger ambitions, including an agentic layer.Key challenges :Evolve the system from a deterministic approach to agentic systems, improving secret-to-company mapping accuracy and impact analysis.Redesign an existing multi-service architecture into a horizontally scalable and maintainable system.Move from batch processing to real-time processing, enabling secrets to be qualified within minutes of detection on GitHub.Extend the pipeline to new public data sources (Docker Hub, NPM, PyPI, etc.), beyond GitHub.Build a search-oriented data architecture capable of handling hundreds of millions of secrets.Scale the system to full dataset coverage, whereas only a subset is currently processed.In short: you will have real ownership over the architectural decisions that will define the next generation of the pipeline.Your

responsibilities :Design and implement the end-to-end data architecture.Build real-time systems, from design through production deployment.Be hands-on on the most complex and critical technical challenges.Design monitoring, maintenance, and alerting systems around the data pipeline.Mentor and raise the technical bar within

the team through code reviews and knowledge sharing.Structure engineering processes and facilitate collaboration across backend, ML, Data, and product teams.Contribute to the technical roadmap in close collaboration with the Engineering Manager and Product Manager.Technical environmentBackend: Python + Django, Go, RabbitMQ, RedisDB: Elasticsearch (+ Kibana), PostgreSQL, ClickHouse, SnowflakeFrontend: React / TypescriptDeployment: Docker, Terraform, AWSAbout youIf you think you match at least 70% of these criteria, please apply!Here's what we consider essential for success in this role:7+ years of experience in data engineering, with a strong track record building and operating large-scale, production-grade data pipelines.Strong expertise in distributed systems and real-time architectures (streaming, event-driven systems).Strong experience with AWS, Terraform, Docker, and Kubernetes in production environments.Strong experience with ClickHouse or similar large-scale analytical databases.Hands-on engineering mindset: ability to contribute directly to production code on critical systems, not just design.Proven experience redesigning or refactoring existing production architectures.Strong ownership mindset: you proactively identify problems and drive solutions end-to-end.Experience mentoring engineers and raising the technical level of a team.Excellent communication skills and ability to work effectively with backend, ML, Data and Product teams.Fluent English in an international environment.The following skills would strengthen your application but aren't required:Experience with large-scale search systems (Elasticsearch, OpenSearch).Familiarity with agentic systems or LLM-based architectures applied to data pipelines.Experience in high-growth startups or scale-ups.The interview process1. Video call with a Talent Acquisition team memberTo discover your professional project and evaluate if there could be a mutual match.2. Interview with Jeremy (Chief Technical Officer) and Alexis (Engineering Manager) (1h)Purpose: To know more about yourself and your achievements, and present to you

the team.Skills Assessed: We assess your soft skills (ownership, communication), motivation and your experience as a tech leader.3. Technical interview with

the team (2h)Purpose: We validate your hard skills and give you the opportunity to discuss with other staff engineers and data engineersSkills Assessed: Python coding proficiency, Data architecture skills and overall communication and reasoning.4.1 Final interview with an Executive ManagerTo detail our company’s vision and ambitions for the next couple of years.4.2 References checkYou 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.

Benefits💰 Package that includes stock-options🍜 Sponsored lunch vouchers (Swile)👟 Sponsored Wellpass (gymlib)🏥 Non-charged health insurance for children (Sidecare / Generali)💻 Up to €300 to improve your home office set-up🌴 Yearly holiday allowance🎡 Team building: monthly budget dedicated to each employee that you can spend as you wish, with colleagues (latest examples to date: Michelin star restaurant, karaoke, stand-up show, kitesurfing week-end, ...)And also...🏡 Remote policy: hybrid (3 days/week at the office in Paris)🤖 Full, company-wide access to cutting-edge AI tools to stay ahead of the curve📈 Opportunities for career development in the long term🤝 Referral

bonus of 4000€ for any new Guardian we might hire thanks to youMore about GitGuardian!StackBackend: Python (Django) Go, RustFrontend: JavaScript (React), TypeScript, React Query, JestDB: PostgreSQL, Elasticsearch (+ Kibana), MongoDBObservability: Elastic Stack, Sentry, Grafana LGTM, OTELDeployment: ArgoCD, GitlabCI, TerraformRuntime: Kubernetes (Karpenter, Istio)Cloud providers: AWS and OVHMessage brokering: RabbitMQ, RedisProductsUnderstand how GitGuardian works in this short video!Want to go even further? Check out our public roadmap!Check out the State of Secrets Sprawl Report to understand our mission and the industry.Our solutions are already used by hundreds of thousands of developers in all industries and GitGuardian platform is the n°1 app on the GitHub marketplace 🔥ClientsGitGuardian helps organizations find exposed sensitive information that could often lead to tens of millions of dollars in potential damage.More than 70% of our customers are in the United States.Many F500 companies use GitGuardian's platform.PeopleThe Guardians are knowledgeable, committed, serious, aligned with the company’s mission, and true team players: always willing to help each other grow our skill sets!

The team is diverse and we hail from more than 20 different countries.We are also agile, remote-friendly, and fun people to work with.You will get trust & autonomy on your perimeter with a very transparent internal communication and a strong impact on the company development.