Senior Data Engineer ( f/m/d) Ajouter aux favoris

IDnow is a leader in digital identity and fraud prevention in Europe with a mission to transform trust into the most powerful asset in the digital world, empowering enterprises with AI-driven, SaaS-based identity solutions that deliver scalable security, adaptive compliance, and real-time fraud prevention .Through its broad portfolio of digital identity and fraud prevention solutions, IDnow establishes, maintains and enriches trust throughout the customer journey, ensuring businesses can confidently and securely operate while leveraging digital identity to drive growth, security and scalability.

The company has offices in Germany, United Kingdom, Romania and France , and is backed by renowned institutional investors, including Corsair Capital and Seventure Partners. Its portfolio of international clients spans a wide range of end markets including financial services, telecommunications, travel & mobility, gaming, and other industries.

This position is based in Rennes, France.

Europe's leader in identity verification solutions (KYC, eSigning, IDcheck, etc.), is strengthening its RDM (Research Data Management) division. We are looking for a Senior Data Engineer passionate about data and industrialization to design and operate the tools and data storage that power our software and AI research. The data you'll manage is at the core of what IDnow does: identity documents, biometric data, and verification records, sensitive by nature, regulated by design, and technically challenging to handle at scale. You will play a key role in the design and construction of our next-generation data lake , shaping its architecture from the ground up and bringing your experience to a team that values technical leadership and ownership.

Key Responsibilities

• Define and own data storage and data management architecture for our software and AI/ML workflows.
• Develop and maintain tools and services that AI & ML R&D teams and engineering teams rely on, including workflow orchestration platforms and test campaign infrastructure.
• Manage and analyze large data volumes.
• Set up and maintain backend APIs and services that provide reliable and secure internal data access.
• Operate and evolve the platform infrastructure (CI/CD, containerization, deployments) with a strong focus on quality (automated testing).
• Enforce data access policies and GDPR compliance rules on research datasets, ensuring proper governance, traceability, and data minimization.
• Collaborate closely with internal stakeholders (ML teams, product design and development, QA, devops) in an agile environment to prioritize and deliver within a continuous improvement process.
• Enforce data access policies and GDPR compliance rules on research datasets, ensuring proper governance, traceability, and data minimization.

Preferred Experience

Required:

• Application development in Python (tooling, services, data scripts, packaging).
• API frameworks and REST APIs (FastAPI/Django REST or equivalent).
• Automated testing with pytest; strong quality and coverage mindset.
• SQL databases: solid knowledge of PostgreSQL and MariaDB (modeling, query writing, migrations, basic performance tuning).
• Data storage: design and operation of data storage solutions, including S3-compatible object storage (Ceph/Rook) .
• Docker and Kubernetes: containerization best practices and cluster deployments.

Strong plus:

• Helm and ArgoCD : we are currently migrating our full stack to a Kubernetes + Helm + ArgoCD deployment model, hands-on experience here is a significant advantage.
• Identity and access management: Keycloak or equivalent SSO/IAM solutions.
• Search & analytics: OpenSearch or equivalent.
• CI/CD: GitLab CI, deployment automation (Ansible, ArgoCD).

Working Environment

• Multidisciplinary teams (AI/ML research, development, QA), agile methodology.
• Internal clients with a direct impact on the speed and quality of AI research at IDnow.
• Strong technical culture, with mutual support and continuous growth.
• A technically rich domain where AI, security, and privacy constraints intersect.
• Linux: day-to-day administration and tooling (shell, security, permissions, networking).

What You'll Bring

• The ability to translate R&D needs into robust, scalable, and well-tested data platforms and tools.
• Technical leadership on data lifecycle management (ingestion, storage, access, traceability) in service of AI and testing.
• The ability to drive key architectural decisions on our data lake: storage organization, access patterns, data lifecycle, and tooling choices.
• An industrialization mindset (automation, reproducibility, observability) applied to ML and data workflows.

Soft Skills

• Motivation and initiative.
• Curiosity, appetite for technical challenges, and continuous learning.
• Team spirit, clear communication with diverse stakeholders (engineers, researchers, QA, devops).
• Rigor, service orientation, and product mindset.
• English required (international environment).

Perks & Benefits

• Health & Wellbeing: Use your full access to the mental health platform nilo, including 1on1 sessions.
• We value personal and professional development: make full use of Udemy, our training platform with 24/7 access and unlimited content/course consumption incl. certification.
• We make your remote work comfy: we provide support on equipment and offer flexible working hours.
• We value collaboration & love to come together: regular onsite gatherings, internal initiatives and summer parties to connect outside of work.
• May your family require your attention or other reasons apply: use the benefit of our paid special leave days.
• Enjoy the possibility to combine work with a longer stay at your holiday destination or extend a weekend with our Workcation possibilities.
• In addition to the perks & benefits above, we offer specific benefits that differ between our locations.

IDnow applies the principles of non-discrimination and equality: We strive to establish, maintain, and promote an open and inclusive recruitment process and working environment by respecting the principles of equal opportunities. Including but not limited to: sex, race or ethnic origin, religion or convictions, gender identity, citizenship, marital status, disability, age, or sexual orientation.