Sr System Program Developer II
Overview
English Version:
This is more than a job. It’s a chance to build, grow, and make a real impact!
We are looking for aSenior Data Architect to join our Data Architecture team and help design, evolve, and deliver our modern data platform.
In this role, you will work closely with the Lead Architect,thedataandAI engineering team,thesystemintegration team, and business stakeholders to build scalable dataand integrations architecture to support our business teams.
You will play a key role in connecting business systems, enabling reliable analytics, accelerating data product development, and preparing the platform for AI/ML use cases.
This is a strategic and hands-on architecture role for someone who enjoys technical design, trade-off analysis, system integration, and pragmatic solution delivery.
Responsibilities
Architecture & Platform Design
- Design and evolve our modern data platform using technologies such asSnowflake,dbt, Python, Airflow, AWS, Fivetran, and Prometheus .
- Define end-to-end data architectures covering ingestion, integration, transformation, modelling, serving, and observability.
- Design scalable data solutions that connect multiple business systems across the software sales and management chain.
- Produce clear architecture documentation and diagrams to support decision‑making and implementation.
- Conduct technical spikes and proof‑of‑concepts to evaluate tools, patterns, and architectural approaches.
- Contribute to data modelling, governance, security, and platform design standards.
Solution Delivery & Engineering Collaboration
- Translate business requirements into scalable, secure, and maintainable data solutions.
- Design end‑to‑end implementation of data solutions from discovery to production.
- Work closely with data engineers, AI engineers, and system developers to ensure architecture is practical and implementable.
- Promote pragmatic engineering practices, including code quality, version control, CI/CD, testing, and maintainability.
- Evaluate trade‑offs across cost, performance, scalability, security, operational complexity, and delivery speed.
Data Strategy & AI Enablement
- Support modern data architecture patterns such asData Mesh, data products, Lakehouse architecture, and event‑driven architecture .
- Ensure the platform can support analytics, feature engineering, model training, GenAI use cases, and AI‑enabled business decision‑making.
- Stay up to date with trends in modern data platforms, cloud architecture, and AI‑enabled ecosystems.
Qualifications
- 6+ years of experience in Data Engineering, Data Architecture, or related roles.
- Strong hands‑on experience with:
- Snowflake
- dbt
- Python
- AWS services such as S3, Lambda, IAM, Glue, etc.
- Fivetran or similar ingestion/integration tools
- Strong understanding of ETL/ELT design patterns and modern cloud data warehouse architectures.
- Experience designing scalable, secure, and maintainable cloud data platforms.
- Experience with data modelling, data integration, and serving data for BI/AI, analytics, or data products.
- Ability to create high‑quality architecture diagrams and technical documentation.
- Strong analytical thinking, structured problem‑solving, and communication skills.
- Ability to explain complex technical concepts to both technical and non‑technical stakeholders.
Preferred Qualifications
- Experience withData Mesh, data products, Lakehouse architecture, or event‑driven architecture .
- Hands‑on experience with other data platforms such asDatabricks,BigQuery, Redshift, or Microsoft Fabric .
- Experience withC4 Model ,TOGAF principles , or architecture governance frameworks.
- Exposure toML/AI data pipelines, feature engineering, model lifecycle, or GenAI‑enabled data products .
- Experience leading end‑to‑end implementation of data solutions.
- Good understanding of software engineering and DevOps best practices.
Desired Certifications
The following certifications are considered a plus:
- dbtcertification, such asdbtAnalytics Engineering Certification
- Snowflake certifications, such as:
- SnowProCore
- SnowProAdvanced: Architect
- SnowProAdvanced: Data Engineer
- AWS certification, especially:
- AWS Certified Solutions Architect – Associate
French Version
Bien plus qu’un emploi, une opportunité de construire, d’évoluer et d’avoir un réel impact !
Nous recherchons un(e) Architecte Data Senior pour rejoindre notre équipe Data Architecture et contribuer à la conception, à l’évolution et à la mise en œuvre de notre plateforme de données moderne.
Dans ce rôle, vous travaillerez en étroite collaboration avec le/la Lead Architect, les équipes Data & AI Engineering, les équipes d’intégration des systèmes ainsi que les parties prenantes métiers afin de concevoir des architectures de données et d’intégration évolutives au service des besoins de l’entreprise.
Vous jouerez un rôle clé dans l’interconnexion des systèmes métiers, la mise à disposition de données fiables pour l’analyse, l’accélération du développement de produits de données et la préparation de la plateforme aux cas d’usage liés à l’intelligence artificielle et au machine learning.
Ce poste combine vision stratégique et expertise opérationnelle. Il s’adresse à une personne appréciant la conception technique, l’analyse des compromis architecturaux, l’intégration de systèmes et la mise en œuvre pragmatique de solutions.
Responsabilités
Architecture & conception de la plateforme
- Concevoir et faire évoluer notre plateforme de données moderne en s’appuyant sur des technologies telles que Snowflake, dbt, Python, Airflow, AWS, Fivetran et Prometheus ;
- Définir des architectures de données de bout en bout couvrant l’ingestion, l’intégration, la transformation, la modélisation, la diffusion et l’observabilité des données ;
- Concevoir des solutions de données évolutives permettant de connecter les différents systèmes métiers tout au long de la chaîne de vente et de gestion des logiciels ;
- Produire une documentation d’architecture claire ainsi que des schémas facilitant la prise de décision et la mise en œuvre ;
- Réaliser des études techniques et des preuves de concept afin d’évaluer des outils, des modèles et des approches architecturales ;
- Contribuer aux standards de modélisation des données, de gouvernance, de sécurité et de conception de la plateforme.