About Achref
With over 6 years of experience in data engineering and cloud architecture, I design and optimize scalable data platforms that turn complex data into actionable insights. Skilled in Python, SQL, Spark, and Azure Cloud, I work with technologies such as Databricks, Data Factory, Informatica, Snowflake, and Stonebranch to build reliable, high-performance data ecosystems.
At Saint-Gobain, I lead the design and deployment of data collection and transformation systems across European factories, using Azure Data Factory, Databricks, Snowflake, and Power BI. I help transition legacy systems to Microsoft Fabric and support a Data Mesh approach across international teams.
During my 3.5 years at Danone France, I contributed to the CORTEX project, creating real-time data pipelines for energy monitoring across global factories. This work improved efficiency and sustainability while reinforcing data governance and automation practices.
I began my career at Uicraft Consulting, developing ETL processes and analytics frameworks for enterprise clients ,an experience that taught me adaptability, client focus, and full data lifecycle management.
Certified by Microsoft Azure, IBM, and Databricks, I’m passionate about building intelligent data systems, solving complex challenges, and continuously learning. I thrive in collaborative environments and believe every challenge is an opportunity to innovate.
Outside work, I’m an explorer and sports enthusiast who has traveled to over 40 countries.
Key Skills: Azure, Databricks, Data Factory,Fabric, Informatica, Synapse, DBT, Snowflake, Python, SQL, Spark, Power BI, Data Architecture, Cloud Engineering, Data Mesh, Automation.
French
Native or bilingual
German
Conversational
English
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- AirliquideAWS Data EngineerENERGY AND UTILITIESDecember 2025 - May 2026 (5 months)Paris, FrancePart of the Primary Production squad within Air Liquide’s Data Factory, working as a Data Lake Engineer on the Asset Performance Management (APM) project, covering Worldwide and Europe scope. Responsible for designing, building, and supporting industrial data products in a multi-country, cloud migration context focused on performance, scalability, and data reliability:
- Contributed to the migration of industrial data products from Azure to AWS (UDP platform) as part of a strategic cloud transformation initiative
- Designed and developed data transformations using dbt on AWS Athena to support BI and industrial performance use cases
- Built and orchestrated end-to-end data pipelines using Apache Airflow (dependencies, scheduling, retries, monitoring) ensuring reliable data delivery
- Participated in the design of data models (star/snowflake schemas, primary/foreign keys) to structure analytical data layers
- Developed advanced SQL queries for large-scale industrial data transformation and optimization
- Supported run activities for APM data products, including incident handling, bug fixing, and functional enhancements
- Collaborated in Agile international squads with Product Owners, Data Engineers, and business stakeholders to deliver data-driven solutions
- Contributed to improving the reliability, performance, and maintainability of industrial data pipelines
TechnologiesAWS (Athena, Snowflake, Glue), dbt, Apache Airflow, SQL, Git, CI/CD (GitLab), Azure (migration source), VS Code, Agile/Scrum, Data Modeling (Star/Snowflake), Industrial Data Platforms - Saint Gobain Distribution Bâtiment FranceAzure Data EngineerRAW MATERIALS INDUSTRYDecember 2024 - Today (1 year and 6 months)Courbevoie, FranceResponsable de la conception et de la mise en œuvre d’une plateforme cloud-native detraitement de données en temps réel, destinée à superviser les opérations industrielles enEurope et en Amérique du Nord au sein du Département IA & Data Analytics – ÉquipeManufacturing (HPS) : Abrasives• Conception et maintien d’un pipeline de données de bout en bout basé sur Azure Event Hubs,Stream Analytics et Azure Data Lake Storage (couches Bronze/Silver/Gold).• Développement de workflows de données évolutifs via les pools SQL serverless d’AzureSynapse pour la création dynamique de tables et la logique de transformation.• Construction et orchestration de pipelines ETL avec PySpark et Azure Data Factory,garantissant des rafraîchissements automatiques quotidiens et une livraison cohérente desdonnées.• Création de vues optimisées et de jeux de données structurés pour les besoins d’analyse et de reporting, facilitant la prise de décision stratégique.• Collaboration dans un environnement international (États-Unis, Brésil, Russie) avec unecontribution active à l’optimisation des performances, à la modélisation des données et à lamise en place de la gouvernance.Technologies: Azure Synapse , Snowflake ,Azure Data Factory, Event Hubs, PySpark, SQL, ADLSGen2, Azure DevOps, Databricks, GitHub, Azure Key Vault, JIRA, Confluence
- CHANELFabric Data EngineerLUXURY GOODSOctober 2024 - December 2024 (2 months)Au sein du programme Orion, participant à la modernisation de l’architecture data de Chanel via Fabric et la mise en place d’un modèle de données unifié pour les domaines Legacy & SSOTTaches :•Conception et développement de datasets Gold et Platinum dans Microsoft Fabric Lakehouse, assurant la standardisation et la fiabilité des données métiers.•Participation active à la mise en place du framework Allure, garantissant une modélisation gouvernée, réutilisable et conforme aux standards d’architecture du groupe.•Intégration de données issues d’Oracle RDS via APIs APEX vers Azure Blob et Fabric, en respectant les normes PANDA et les bonnes pratiques du Lakehouse.•Construction et optimisation de pipelines de transformation en PySpark/Delta, incluant règles de qualité, contrôles de schéma et monitoring automatisé.•Harmonisation des données cross-domain et consolidation des logiques métiers pour alimenter une SSOT fiable et exploitable par les équipes Finance, Supply Chain et Manufacturing.•Collaboration étroite avec les équipes architecture, produit et data analytics pour définir l’urbanisation des données, améliorer les performances et garantir la cohérence des modèles.•Contribution à l’évolution de l’écosystème analytique via MS Fabric, notamment l’uniformisation des pratiques de développement et la mise en place des couches avancées (Platinium)Technologies : Microsoft Fabric (Lakehouse, Delta, Notebooks, Data Factory), Azure Blob Storage, Oracle APEX APIs, PySpark, SQL, GitHub, PANDA, DevOps, JIRA, Confluence
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Education
- Master international en intelligence artificielle et Big DataUniversité Paris 13Matières principales : Cloud Computing, IA, Big Data, Data Science, Data engineering, data mining, Mathématiques, Modélisation
- Engineering degree, Computer Software EngineeringEcole Nationale d'Ingénieurs ENISOEngineering degree, Computer Software Engineering