Data Science Engineer - Microsoft Fabric & ETL Pipelines

Casablanca, Casablanca-Settat

Publié il y a moins de 166 jours

Décryptage du poste par Postule AI

Résumé du rôle

A2MAC1 seeks an experienced Data Science Engineer to join its Data & Insights team in Casablanca. You will design and maintain scalable ETL/ELT pipelines using Microsoft Fabric, develop data warehouse architectures, and collaborate with cross-functional teams to enable high-performance analytics and machine learning workflows. This key position requires 3+ years of production-grade experience with Microsoft Fabric, Python, SQL, and data transformation libraries, plus fluency in English.

Exigences clés (estimation)

Design, build, and maintain robust ETL/ELT data pipelines using Microsoft Fabric tools
Develop scalable data warehouse architecture for analytics and reporting
Ensure data quality, security, and compliance across the data lifecycle
Collaborate with cross-functional teams (Data Science, AI, Product, Engineering)
Monitor and improve performance of data processing pipelines
Integrate structured and unstructured data from multiple sources

Compétences

Microsoft Fabric ecosystem (OneLake, Data Factory, Data Warehouse, Synapse)Python, SQL, and data transformation libraries (Pandas, PySpark)ETL/ELT pipeline design and implementationData modeling and performance optimizationProblem-solving and attention to detailEnglish fluency (written and verbal)

Niveau estimé

Mid-level professional with 3+ years of proven experience in production-grade data engineering environments. You should have demonstrated expertise in building and maintaining complex data pipelines and architectures at scale.

Attributs détectés par l’IA (si absents de l’offre)

Type de poste: full-time
Mode de travail: HybrideConfiance 100%
Niveau d'expérience: 3–5 ansConfiance 90%
Fonction: Data / BIConfiance 95%
Secteur: AutomobileConfiance 95%
Niveau d'études: Licence / Bac+3Confiance 70%
Langues: Anglais, FrançaisConfiance 90%

Cette analyse a été générée automatiquement par Postule AI à partir de l'offre.

About the Role

Join A2MAC1's Data & Insights team in Casablanca as a Data Science Engineer. You will design, build, and maintain scalable data pipelines and architectures while enabling high-performance analytics and machine learning workflows. Working closely with engineering, product, and AI/ML teams, you'll deploy advanced data solutions using the Microsoft Fabric ecosystem to drive business insights and support strategic decision-making.

Key Responsibilities

Design, build, and maintain robust ETL/ELT data pipelines using Microsoft Fabric tools
Develop scalable data warehouse architecture for analytics and reporting
Collaborate with cross-functional teams (Data Science, AI, Product, Engineering)
Ensure data quality, security, and compliance across the data lifecycle
Integrate structured and unstructured data from multiple sources
Leverage Python and open-source libraries to enhance data workflows
Monitor and improve performance of data processing pipelines
Apply best practices in data governance and version control

Required Skills & Experience

Hands-on experience with Microsoft Fabric ecosystem: OneLake, Data Factory, Data Warehouse, Synapse
Strong proficiency in Python, SQL, and data transformation libraries (Pandas, PySpark)
Proven experience designing and implementing ETL/ELT pipelines
Solid understanding of data modeling and performance optimization
3+ years of experience in a production-grade environment
Fluent in English (written and verbal)

Nice to Have

Familiarity with machine learning workflows and tools (Azure ML, Scikit-learn, MLflow)
Experience with Power BI and data visualization best practices
Exposure to DevOps concepts and tools (CI/CD, Azure DevOps)
Relevant certifications (DP-203, DP-900, or equivalent)
Fluency in French

About A2MAC1

A2MAC1 is the leading provider of automotive benchmarking and data analytics worldwide. With 700+ employees across Europe, Asia, and North America, we help OEMs and suppliers understand their competitive landscape and make better strategic decisions through reliable, structured, and actionable insights.

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