Data Engineer

• You will join the engineering team to take part in the design and development of these agent-driven applications:
• Structuring agents,
• Integrating them with our existing data and systems,
• Implementing tests and safeguards,
• Deploying to the Cloud (Google Cloud Platform).
• You will also use generative AI tools as daily development accelerators — a common practice within the team.
• Your mission will include experimenting with and evaluating how these tools (Cursor, Claude Code, Copilot...) can optimize each stage of our projects: design and architecture, test automation, code review, documentation and deployment.
• Depending on the team’s needs, you may also work on data topics (processing, structuring data) and cloud topics (deploying applications on Google Cloud Platform).
• By the end of your internship, you will have learned how to design and industrialize an application based on AI agents, integrate it cleanly into a production environment, process data natively in the Cloud, and gain hands-on experience deploying applications on Google Cloud Platform.

Data & AI Engineer Intern

• Connecter et intégrer des données issues de systèmes RH, IAM et ITSM
• Concevoir et développer des pipelines ETL/ELT en batch et en streaming
• Construire des modèles de données unifiés autour des identités et des habilitations
• Réaliser les mappings entre utilisateur·rice·s, rôles, droits d'accès et applications
• Participer à la mise en œuvre d'un Identity Graph offrant une vision consolidée des identités et des accès
• Définir et automatiser les contrôles de qualité des données IAM
• Identifier les comptes orphelins, doublons et incohérences entre référentiels
• Mettre en place des indicateurs de fraîcheur et de complétude des données

Senior Data Engineer, IAM

• Participate in data processing, transformation and delivery to internal teams
• Improve the performance of our clients' campaigns and marketing strategies
• Be passionate about data in all its forms
• Want to understand data and extract insights from it
• Take pride in high-quality work and have an eye for detail
• Work for a diverse range of prestigious clients
• Stay up to date with new languages/technologies and open-source trends
• Collaborate with different data disciplines
• Have an interest in Marketing and explore this field

• Architect and optimize the cloud data infrastructure to support Purse’s growing data/AI needs
• Design and evolve high-performance data pipelines: large-scale ingestion, transformation and orchestration for payment streams
• Ensure data quality, traceability and compliance (GDPR, payment data security)
• Act as a technical partner to Tech, Product, Business and AI teams, translating functional requirements into robust, scalable solutions
• Actively contribute to the team’s data maturity: best practices, documentation, code reviews

• Design, build, and maintain data infrastructures
• Ensure data quality, availability, and performance
• Develop ETL/ELT pipelines
• Clean, structure, and validate data
• Industrialize data solutions (CI/CD, MLOps)
• Collaborate with Data Scientists, Data Analysts, and IT teams
• Propose data solutions tailored to specific use cases

• Design, build, and maintain robust data pipelines
• Model data for analytics, BI, AI, and self-service use cases
• Build Bronze, Silver, Gold, Semantic Layer, and Exposition Layer data models
• Transform complex business problems into simple, durable, and scalable data products
• Contribute to reactivity, freshness, and near-real-time data needs
• Implement a complete Tech Flow based on an “as-code everywhere” approach
• Improve the quality, performance, governance, and observability of data pipelines

AI-Augmented Data Engineer

• Contribute to the design, development, and operation of IDEMIA's enterprise Data Platform and GenAI Platform on AWS
• Build scalable data products, industrialize data pipelines, and support the development of AI and Generative AI capabilities across the Group
• Design, develop, and maintain scalable batch and near real-time data pipelines
• Build and optimize ETL/ELT processes on AWS and Apache Spark
• Develop and maintain data products supporting Analytics, BI, Data Science, and GenAI use cases
• Contribute to the evolution of IDEMIA's Lakehouse architecture
• Ensure data quality, governance, lineage, security, and performance
• Participate in the development of the enterprise GenAI platform
• Collaborate with Data Scientists and AI Engineers to industrialize AI and GenAI solutions
• Contribute to CI/CD, Infrastructure-as-Code, observability, and DataOps best practices

Senior Data Engineer

• Intégration de l'équipe Data d'un grand groupe du secteur bancaire et financier
• Accompagner les projets sur la collecte, la transformation, le stockage et la mise à disposition de données
• Concevoir et déployer les outils et pipelines CI/CD
• Développer et implémenter des mécanismes de contrôle qualité
• Participer activement à la conception technique et fonctionnelle des solutions de stockage
• Assurer le support technique, l'analyse et la résolution des incidents

• Ship and operate production pipelines across batch, streaming, and reporting stacks, from requirements to monitoring
• Design storage and compute for petabyte-scale datasets using Iceberg, Spark, DuckDB, and Trino
• Cut cost and latency on specific pipelines and queries, with quantified, instrumented impact
• Own the data contract for the ClickHouse and Cube reporting stack behind the Clear UI
• Build alerts, SLOs, and runbooks so fewer incidents reach users
• Lead incident response and carry on-call across production systems
• Influence upstream producers on schemas, semantics, and SLAs for bid, win, and impression events
• Build tooling, conventions, and data contracts that make the whole team faster

• Design and evolve data processing on an Azure Lakehouse architecture.
• Collect, integrate, structure, and model data.
• Optimize processing performance and ensure data quality.
• Prepare datasets for analytics and AI use cases.
• Promote AI-assisted development practices including code generation, refactoring, testing, and documentation.
• Provide technical expertise to support data projects in an international transformation context.

Senior Data Engineer, AI

• Design and evolve data processing pipelines on an Azure Lakehouse architecture.
• Participate in the collection, integration, structuring and modeling of data.
• Optimize processing performance and ensure data quality.
• Prepare datasets for analytical consumption and AI projects.
• Promote and improve AI-assisted development practices (code generation, refactoring, testing and documentation).
• Support Data projects by providing your technical expertise.

• Join the Data team to contribute your technical expertise
• Implement and optimize data feeds and data pipelines
• Work in tandem with a Data Analyst on AI and data use cases
• Develop and integrate AI agents for SQL querying
• Maintain an active technology watch on modern data architectures

• Contribute to the design and build of a modern, scalable data platform from greenfield — participate in decisions on cloud infrastructure, data ingestion, transformation, storage, and serving layers
• Apply and help refine data modeling standards, pipeline patterns, ingestion frameworks, and governance practices
• Help ensure the platform meets HIPAA and GDPR compliance requirements and incorporate those constraints into your work
• Support the full project lifecycle for platform initiatives: help define scope, track timelines, manage dependencies, and deliver with a bias for action
• Proactively identify gaps and risks in the data landscape — bring problems to the table with proposed solutions
• Drive tasks end-to-end: take ownership, manage your own blockers, and follow through
• Partner with the broader data engineering function and contribute as a collaborative technical voice on platform direction
• Translate business and clinical data needs into technical implementation, balancing pragmatism with long-term scalability
• Collaborate with stakeholders across Sweden, the UK, the US, and local markets — strong asynchronous communication and comfort operating across time zones required
• Establish and optimize data models and architectures (e.g., lakehouse, data warehouse, data mesh) to support enterprise-wide data accessibility and performance
• Proactively identify gaps, risks, and opportunities in the data landscape — present problems with solutions, not just observations
• Comply with company and departmental policies and administrative requirements
• Perform other duties as assigned or needed

Data Engineer – Data Platform

• Vous servirez de passerelle entre une architecture technique complexe et la valeur commerciale stratégique.
• Vous serez la principale autorité technique pour nos clients.
• Agir en tant que partenaire stratégique principal auprès des responsables métiers clients.
• Piloter le développement d'architectures de données complexes et à grande échelle.
• Superviser les performances de livraison de plusieurs équipes.
• Diriger le tri et la résolution des incidents critiques de la plateforme.
• Mettre en œuvre des cadres de gouvernance robustes et des contrôles de conformité.
• Promouvoir une culture organisationnelle de partage des connaissances.
• Influencer la santé à long terme de l'organisation.

Principal Data Engineer – Contractuel

• Delivery / Conseil & Expertise: Conception et mise en œuvre d'architectures Data modernes (Cloud & On-premise)
• Réalisation d’audits, définition de roadmaps, accompagnement sur les choix technologiques
• Réalisation de PoC/MVP, coaching technique, conduite du changement
• Participation à l’écosystème tech (Meetups, afterworks, partenaires, éditeurs…)
• Contribution active à notre communauté d’experts Data (Snowflake, AWS, GCP, Azure, Databricks, DBT, Looker, Rivery, Airbyte, etc.)
• Accompagnement des équipes commerciales sur les réponses techniques
• Participation à la formalisation des offres et des convictions Data de l’agence
• Accompagnement de consultants en mission, animation de la communauté, recrutement, entretiens techniques

Data Architect

• Conceive, develop and industrialize reliable and high-performance data pipelines
• Integrate structured and unstructured data, both in batch and real-time
• Deploy and optimize data environments on the Cloud (AWS, Azure, GCP)
• Implement and orchestrate ETL/ELT processes (Talend, Airflow, dbt, Fivetran, etc.)
• Work on modern environments such as Databricks, Snowflake, BigQuery, Redshift
• Ensure data quality, security and governance
• Contribute to technology watch and recommend the best solutions for each project

• Build a clear understanding of Vibe’s key data flows, sources of truth, and ownership.
• Help define schemas, data contracts, documentation, and standards for how data should be used across the company.
• Improve data discoverability so teams can confidently understand what data exists, where it lives, and how to use it.
• Establish practical standards around data quality, lineage, observability, and ownership.
• Define, maintain and enforce data lifecycle policies.
• Help teams track data cost and usage.
• Define and implement data compliance practices aligned with Vibe’s business, partners, and regulatory needs.
• Partner with Legal, Product, Security, and Engineering to assess the impact of new data sources, partnerships, and use cases.
• Help clarify what data can be used, how it can be used, where it should live, and how long it should be retained.
• Support Vibe’s ability to work confidently with premium publishers, enterprise advertisers, and strategic partners.
• Build guardrails, not gatekeepers, enabling engineers and teams to move fast while making safe, compliant decisions.
• Embed governance and compliance into existing engineering workflows, tools, and architectural decisions.
• Help Vibe transition toward a more security, and compliance-aware, data culture.
• Identify the biggest risks, gaps, and opportunities, then define a pragmatic roadmap to address them.

Principal Data Engineer – Governance & Compliance

• Design and develop data ingestion, processing, and modeling pipelines using DBT
• Optimize SQL queries on BigQuery to ensure data performance and reliability
• Model the semantic layer with Looker/LookML to enable business users to leverage the data
• Automate workflows using GitLab CI/CD and Docker Compose
• Collaborate in an Agile (Scrum) environment with technical and business teams to deliver high-value data solutions

Data Engineer jobs in France

See all jobs on JobTailor

Data & AI Engineer Intern

Senior Data Engineer, IAM

Data Engineer

Data Engineer

Data Engineer

AI-Augmented Data Engineer

Senior Data Engineer

Data Engineer

Data Engineer

Senior Data Engineer, AI

Senior Data Engineer, AI

Data Engineer

Data Engineer – Data Platform

Principal Data Engineer – Contractuel

Data Architect

Data Engineer

Principal Data Engineer – Governance & Compliance

Data Engineer, DBT, SQL