Data Engineer Jobs in Paris, EEA

En quête d’un collectif pionnier, en mode Test & Learn permanent, qui donne réellement les moyens de vos ambitions ? Ne cherche plus ! Chez SFEIR, aucune évolution n’est imposée : tu pilotes ton propre parcours — qu'il soit vertical, horizontal ou transverse  💻 Ton Terrain de Jeu Stack : Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Cloud Composer), Python, SQL, DBT  SFEIR AI : Un parcours dédié pour maîtriser l'IA générative et le coding agentique Communauté : 140 certifiés Google Cloud, 30 Google Authorized Trainers, 7 Google Developer Experts  🚀 Tes missions  Concevoir et développer des pipelines de données robustes et scalables sur GCP  Implémenter des solutions ETL/ELT avec DBT sur BigQuery  Orchestrer des workflows data avec Cloud Composer  Mettre en place du monitoring et de l'observabilité des plateformes data  Participer à la modernisation des architectures data de nos clients 🎯 Ton profil Tu as au moins 3 ans d’expérience en tant que Data Engineer  Tu as une expérience professionnelle confirmée sur Google Cloud  Tu es passionné(e) par la Data et l’IA : tu fais de la veille et tu as des projets persos  Tu souhaites relever des défis de haut vol tout en évoluant dans un environnement stimulant  💙 Pourquoi rejoindre SFEIR ?  Chaque Sfeirian est accompagné(e) par un Engineering Manager  Evolution vers des rôles de Lead Data ou Data Architect  Formation continue avec accès à Google Cloud Skills Boost et certifications Participation aux évènements Google CloudCommunauté active avec plus de 50 événements annuels 🛠 Ton Pack Sfeirian Équipement au choix : MacBook Pro ou Dell Precision  Prime Vacances : 10% de la valeur des congés pris Prime de participation  Télétravail : mode hybride 5 semaines de congés + 8 à 12 RTT/an Carte ticket restaurant (11€/jour) Mutuelle et prévoyance Abonnement navigo ou remboursement de 70% pour un vélo électrique CSE : participation sports / culture / loisirs, chèques-cadeaux, activités (ski, golf, futsal, ...) Teamstarter : SFEIR verse 10€ par mois sur ta cagnotte personnelle pour financer des projets associatifs ou solidaires

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75. Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ Join us as a Data Engineer (ML Infrastructure) to build the data layer that powers Qonto's machine learning products. Working alongside 15 ML Engineers, you will own the pipelines, feature stores, and model serving infrastructure that turn raw financial data into production-grade ML — so engineers spend their time on models, not plumbing. You will report to Marianne Borzic or Benjamin Wolter — see manager section below. ➡️ What you'll do Build and own ML data pipelines: Design, implement, and maintain Python pipelines that ingest, transform, and deliver datasets for model training and inference — covering use cases like [fraud detection / credit scoring / accounting automation — confirm with HM]. Own the feature store: Design storage and access patterns for large-scale feature datasets, balancing latency and cost so ML Engineers can retrieve features reliably at both training and serving time. Drive model serving infrastructure: Implement and maintain the infrastructure that deploys trained models into production, including versioning, scaling, and rollback. Build data quality and drift detection systems: Work with ML Engineers to catch data issues before they degrade model performance in production — making reliability a shared standard, not an afterthought. Set the data engineering standard: Establish reusable Python and pipeline patterns the team builds on — creating foundations, not one-off solutions. ➡️ What we're looking for ML infrastructure experience: You've built pipelines and infrastructure that directly supports machine learning workflows — not just ETL. You understand what feature stores, model registries, and serving layers are and why they matter. Python at scale: You're fluent in Python for data engineering and have solid experience with [Spark / dbt / Airflow / Ray — confirm stack with HM]. You write code others can maintain. ML workflow understanding: You don't build models, but you understand the full ML lifecycle — training, validation, deployment, monitoring — well enough to build the infrastructure that serves each stage. Systems thinking: You design data architectures that balance today's needs with tomorrow's scale, treating cost, latency, and reliability as first-class constraints. Production mindset: You've operated data systems in production. You know what breaks and how to prevent it. ➡️ What we can offer you Direct impact at scale: Your pipelines feed models that process transactions for SMEs and freelancers across Europe. When you improve data quality or reduce feature latency, it shows up directly in product. A rare team configuration: 3 Data Engineers working alongside 15 ML Engineers — a ratio that means your infrastructure work is immediately stress-tested by the people who depend on it most. Build, don't inherit: Qonto's ML infrastructure is still being built. You won't be handed a legacy system — you'll define how it's done, with real ownership over architectural decisions. Fast iteration cycle: We work with continuous delivery, so infrastructure improvements ship frequently and you see their impact quickly — not in a quarterly release. Cross-functional exposure: You'll work at the intersection of data engineering, ML, and product, contributing to financial solutions for SMEs across France, Germany, Italy, Spain, and beyond. ➡️ Your future manager Option A Your manager will be Marianne Borzic Ducournau, Head of Data Products. Her background? A graduate of École Polytechnique, Marianne went on to lead Data Science teams at Uber and Amazon in San Francisco before joining Qonto four years ago to build our Data Science team from scratch — hiring the founding members and defining the technical direction. What does she bring to the team? A rare combination of applied ML expertise and business context from Finance — she helps people see both the technical and the strategic side of what they're building. Option B Your manager will be Benjamin Wolter, Head of AI Products. His background? After earning his PhD in Physics and leading ML Engineering and Data Science teams across last-mile logistics and digital marketing, Benjamin joined Qonto to lead our AI Products team. What does he bring to the team? Deep technical ML expertise, practical experience building scalable ML systems, and a management style built around ownership and autonomy — he creates the conditions for people to grow without hand-holding.

Join Pigment: The AI Platform Redefining Business Planning   Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team—from Finance to HR—to build, adapt, and align strategic plans in real time.   Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario.   With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner® Magic Quadrant™ for Financial Planning Software.   At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo—all while working as one team. If you're driven by innovation and ready to make an impact at scale, we’d love to hear from you. What You’ll Do:   We’re looking for a talented engineer to join Pigment’s Growth team. We operate as a Product Team inside the Revenue organization, focused on building GTM systems rather than just looking for the next growth hack.   Our small team designs and ships high-impact internal systems used by 100+ internal users every week. We build and maintain a centralized GTM data warehouse, internal web applications, orchestration workflows, and AI agents. These systems are treated like real products - with users (internal teams), adoption metrics, feedback loops, and continuous iteration.   It’s also a unique opportunity to collaborate with amazing brains across Sales and Marketing as end users, RevOps and Data team as key stakeholders for everything systems and data governance, and even our R&D team on AI engineering.   To give you an idea of projects we built, you can check this article here. 

Since 2012 Odaseva has helped global enterprises secure and manage their most valuable asset: data. The Odaseva EnterpriseData Platform secures and manages Salesforce data, ensuring data resilience, regulatory compliance, and unlocking the value of data. It’s built to solve the complex challenges of large-scale global enterprises.  We’re a fast-growing scale-up with offices in San Francisco, Paris, Sydney, London, Kuala Lumpur, Singapore, and more. We serve a global customer base including Fortune 500 companies, government organizations, and NGOs supporting more than 100 million Salesforce users worldwide. At Odaseva, our values, Trust, Service, Commitment, Excellence, Kaizen, and One Team, define the environment we foster for our employees to thrive and succeed. Join Odaseva’s R&D team and help shape the future of our data platform. We’re a SaaS company specializing in secure data management around Salesforce environments. You’ll design, build, and optimize scalable data pipelines and help kick-start our first AI use cases.

About Mistral    At Mistral AI, we believe in the power of AI to simplify tasks, save time and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.   We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.   We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.   Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.   Role summary We are seeking passionate and talented Data Engineers to join our team. Candidates with an Analytics Engineering background are also encouraged to apply. In this role, you will have the unique opportunity to build, optimize, and maintain our data infrastructure. You will work with large volumes of data, enabling product teams to access secure and reliable data quickly. Your contributions will support our science team in enhancing the quality of our state-of-the-art AI models and help business users make informed decisions.   What you will do • Design, build, and maintain scalable data pipelines, ETL processes, and analytics infrastructure. Automate data quality checks and validation processes. • Collaborate with cross-functional teams to understand data needs and deliver high-quality, actionable solutions, eg work closely with machine learning teams to support model training, deployment pipelines, and feature stores. • Optimize data storage, retrieval, processing, and queries for performance, scalability, and cost-efficiency. • Define and enforce data governance, metadata management, and data lineage standards. • Ensure data integrity, security, and compliance with industry standards.   About you • Master’s degree in Computer Science, Engineering, Statistics, or a related field. • 3+ years of experience in data engineering, analytics engineering, or a related role. • Proficiency in Python and SQL. • Experience with dbt. • Experience with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Clickhouse). • Strong analytical and problem-solving skills, with attention to detail. • Ability to communicate complex data concepts to both technical and non-technical stakeholders.   Nice to Have • Experience with machine learning pipelines, MLOps, and feature engineering. • Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes). • Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform). • Background in building self-service data platforms for analytics and AI use cases. Hiring process • Intro call with Recruiter - 30 min • Hiring Manager Interview - 30 min • Technical interview - Live Coding (Python/SQL) - 45 min • Technical interview - System Design - 45 min • Value talk interview - 30 mins • References   By applying, you agree to our Applicant Privacy Policy.  

Chez MARGO, nos consultants travaillent sur ce qui compte vraiment : des projets complexes qui allient challenge intellectuel et impact business réel.C’est pourquoi nous accompagnons les plus grands acteurs de la finance, de l’industrie et de la tech sur leurs projets les plus stratégiques en Data Science, Machine Learning et Intelligence Artificielle. Vos missions Nous recherchons un Senior Data Engineer pour participer à la construction d’une plateforme Data développée from scratch, destinée à des équipes travaillant sur des problématiques de recherche et de calcul intensif. L’objectif de cette plateforme est de gérer l’ensemble du cycle de vie des données : ingestion, traitements distribués, backtesting à grande échelle et mise à disposition des données pour des usages de recherche et de production. L’un des enjeux techniques majeurs du projet concerne le calcul distribué et l’intégration de Spark au cœur de l’architecture de la plateforme. Dans ce contexte, vous interviendrez notamment sur : le développement des composants de calcul distribué, la conception et l’optimisation de pipelines de données à forte volumétrie, les problématiques de performance et de scalabilité liées aux traitements massifs, l’évolution de l’architecture Data, la qualité et la maintenabilité du code Python utilisé en production. Pourquoi rejoindre la practice ? Vous rejoindrez une practice en pleine construction, portée par une forte ambition technologique autour des infrastructures cloud, des plateformes data et des systèmes distribués. L’objectif n’est pas simplement d’accompagner des projets, mais de construire une communauté d’ingénieurs capables d’intervenir sur des sujets techniques exigeants : architecture cloud, calcul distribué, plateformes data, performance et scalabilité. Vous évoluerez dans un environnement où l’autonomie, la profondeur technique et la capacité à prendre des responsabilités sont valorisées dès le départ. Profil recherché Vous maîtrisez Python et accordez une attention particulière à la qualité du code et à la conception logicielle Vous possédez une compréhension approfondie de Spark et des problématiques réelles de calcul distribué Vous avez déjà travaillé sur des systèmes à forte volumétrie ou à fortes contraintes de performance Vous êtes à l’aise dans des environnements cloud modernes Ce que nous offrons Des missions ambitieuses et variées, toujours sélectionnées pour leur valeur ajoutée ; Un accompagnement de proximité par des experts reconnus ; Une communauté d’ingénieurs passionnés, avec workshops, conférences et échanges réguliers ; Une culture d’exigence technique, de partage des connaissances et de développement continu. La suite ? Premier entretien : Échangez avec un recruteur et un business developer Entretien Technique : Montrez vos compétences et recevez un retour d'expérience Entretien de Motivation : Rencontrez un membre du comité de direction

QUI SOMMES NOUS? Chez MARGO, nos consultants travaillent sur ce qui compte vraiment : des projets complexes qui allient challenge intellectuel et impact business réel. C’est pourquoi nous accompagnons les plus grands acteurs de la finance, de l’industrie et de la tech sur leurs projets les plus stratégiques en Data Science, Machine Learning et Intelligence Artificielle. POURQUOI REJOINDRE LA PRACTICE CT? Vous évoluerez au sein d’une équipe encadrée par un Practice Manager CT chez MARGO, également en mission chez un de nos clients.  Travailler à ses côtés, c’est intégrer une équipe d’experts passionnés, être challengé sur le plan technique et méthodologique, et contribuer à des projets à fort impact pour les clients. VOS MISSIONS ? Nous recherchons actuellement un Data Engineer pour intervenir chez un de nos clients du secteur de l’énergie au sein d’un pôle data transverse. Le périmètre couvre l’ensemble des use cases émanant des différents métiers (trading, data, RH, etc). Son rôle est de fournir les briques IT et Data fondamentales qui servent à l’ensemble des équipes. Concrètement, l’équipe recrute des Data Engineers et profils Data capables d’intervenir sur ces projets transverses à fort impact. Principales missions :  - Accompagnement des autres équipes dans leurs projets data/IA - Interventions transversales pour accélérer et industrialiser les use cases - Déploiement et mise en production de projets data/IA - Travailler sur des technologies modernes et monter en compétences sur le cloud AWS - Impact direct sur des sujets concrets tels que la transition énergétique, le mix énergétique, l’écologie, des sujets qui ont du “ sens “  - Haut niveau des collaborateurs (séniorité élevée) - Enjeux d’optimisation continue - Grosse volumétrie de données et variété de données  - Participation à un virage DATA   PROFIL RECHERCHE ? Nous cherchons des ingénieurs et data engineers exigeants, passionnés par la tech et souhaitant évoluer dans des environnements complexes. - Diplômé(e) d’une école d’ingénieur ou d’un cursus universitaire Bac +5 / Master ; - Maîtrise de Python, PySpark, Scala, AWS, Databricks et Sql - Bon niveau d’anglais pour évoluer dans un environnement international. CE QUE NOUS OFFRONS ? - Des missions ambitieuses et variées, toujours sélectionnées pour leur valeur ajoutée ; - Un accompagnement de proximité par des experts reconnus ; - Une communauté d’ingénieurs passionnés, avec workshops, conférences et échanges réguliers ; - Une culture d’exigence technique, de partage des connaissances et de développement continu. LA SUITE ? Premier entretien : Échangez avec un recruteur et un business developer Entretien Technique : Montrez vos compétences et recevez un retour d'expérience Entretien de Motivation : Rencontrez un membre du comité de direction Si cette description vous parle, postulez maintenant ! Découvrez également nos autres opportunités si vous ne vous reconnaissez pas dans cette offre. ENGAGEMENT POUR L'INCLUSION MARGO s'engage à offrir des opportunités égales à tous, nous cultivons un environnement de travail inclusif qui valorise la diversité. ENGAGEMENT POUR L'INCLUSION MARGO s'engage à offrir des opportunités égales à tous, nous cultivons un environnement de travail inclusif qui valorise la diversité.

Alice & Bob is developing the first universal, fault-tolerant quantum computer to solve the world’s hardest problems. The quantum computer we envision building is based on a new kind of superconducting qubit: the Schrödinger cat qubit 🐈‍⬛. In comparison to other superconducting platforms, cat qubits have the astonishing ability to implement quantum error correction autonomously!   We're a diverse team of 250+ brilliant minds from over 35 countries united by a single goal: to revolutionise computing with a practical fault-tolerant quantum machine. Are you ready to take on unprecedented challenges and contribute to revolutionising technology? Join us, and let's shape the future of quantum computing together! About the Role: As a Senior Data Engineer, you will help build and scale our GCP Data Platform, reporting directly to the Data Platform Lead. You will own the full data lifecycle—from building our data lake and architecting ingestion pipelines for quantum computing experiments, to powering company-wide analytics and ML. In this role, you will drive platform infrastructure, data governance, quality, and engineering best practices.

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We’re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace. Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence. Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We’ve built a product customers love and a business that’s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines. At Aircall, you’ll join a company in motion. We’re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth. How we work at Aircall: We’re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you’ll feel at home here. We are looking for an engaged and passionate Senior Data Engineer to join our growing Engineering Team. In this role, you will be a key member of the team managing our analytics and event platform stack. As part of the Analytics & Data Platform team, you will build features for over 22,000 customers across the globe. Your work will unlock the value of data, empowering our customers to make informed decisions through real-time insights, monitoring, and comprehensive analytical reports.

Data Engineer at Airapps. Apply via Ashby.