Emagine is seeking an experienced Senior AI Data Engineer / Azure Data Architect to join a strategic project with a client leveraging advanced analytics and AI/ML initiatives. This role is key in designing, building, and optimizing scalable, secure, and high-performance data pipelines and architectures to support AI-driven business solutions.
This is an excellent opportunity to work on high-impact projects, collaborating with cross-functional teams in a dynamic and international environment.
Your main responsibilities:
Data Engineering & Architecture
- Design, build, and maintain scalable data pipelines on Microsoft Fabric (Data Factory, Dataflows, Lakehouse, Warehouse, OneLake).
- Develop robust data ingestion, transformation, and orchestration processes using Azure Data Factory, Azure Databricks, Azure Synapse, and Azure Functions.
- Implement and optimize Delta Lake architectures for structured and unstructured data.
- Build reusable data products to support AI, machine learning, and analytics workloads.
AI & Advanced Analytics Integration
- Partner with Data Scientists and ML Engineers to operationalize models using Azure Machine Learning, Fabric Data Science experiences, or Databricks.
- Prepare and feature-engineer datasets tailored for AI workloads.
- Automate MLOps workflows, including model monitoring and deployment pipelines.
Governance, Quality & Security
- Implement data quality frameworks, observability, monitoring, and lineage using Fabric and Azure Purview.
- Ensure compliance with governance, data privacy, and security standards.
- Manage CI/CD pipelines for data code using Azure DevOps or GitHub.
Collaboration & Stakeholder Engagement
- Collaborate with business analysts, product owners, and domain experts to understand requirements and deliver high-value data solutions.
- Maintain documentation of data sources, data models, pipelines, and best practices.
- Provide technical guidance and mentorship to junior developers.
You bring:
- Proven experience as a Data Engineer, AI Engineer, or similar role.
- Strong hands-on experience with Microsoft Fabric (Lakehouse, Data Engineering, Data Factory, Data Pipelines).
- Expert knowledge of Azure Data Services:
- Azure Data Factory
- Azure Databricks / Spark
- Azure Synapse / SQL Pools
- Azure Storage (ADLS Gen2)
- Azure Functions
- Azure Machine Learning
- Proficiency in Python and SQL for data processing and transformation.
- Experience building data lakehouse architectures and Delta Lake pipelines.
- Familiarity with modern DevOps/MLOps practices, including version control, testing, and automated deployment.
- Experience with data governance frameworks using Azure Purview or Fabric governance.
- Strong communication, collaboration, and stakeholder management skills.
- Good English proficiency (spoken and written).
Nice to have:
- Experience with enterprise-scale AI/ML projects.
- Exposure to multi-cloud data architectures.
- Previous experience mentoring or leading junior engineers.