Senior Data Engineer

Our requirements

• Hands-on experience in designing, building, and maintaining data platforms, particularly Microsoft Fabric or similar solutions.
• Experience in Data Engineering, including data pipeline design, data transformation, and orchestration.
• Strong understanding of Lakehouse architecture, Data Warehousing, and data modeling.
• Experience implementing AI, Machine Learning, and Generative AI solutions.
• Knowledge of Large Language Models (LLMs), vector databases, embeddings, prompt engineering, and Retrieval-Augmented Generation (RAG) architecture.
• Experience with Microsoft AI technologies, including Azure AI Services, Azure OpenAI, Microsoft Copilot, and AI capabilities within Microsoft Fabric.
• Ability to design and build data solutions that support AI and Machine Learning workloads.
• Proficiency in Python, Spark, SQL, and data analytics/AI libraries.
• Knowledge of MLOps and AIOps, including model deployment, monitoring, and lifecycle management.
• Experience integrating systems through APIs, file-based interfaces, and event-driven architectures.
• Hands-on experience with Azure DevOps, including repositories, work item management, and deployment pipelines.
• Ability to manage services throughout their entire lifecycle, from design and implementation to maintenance and continuous improvement.
• Strong troubleshooting skills related to data platforms, integrations, and AI services.
• Ability to produce clear and well-structured technical documentation.
• Understanding of security best practices, access control, and data governance.
• Knowledge of Responsible AI principles, AI model governance, and ethical AI practices.
• Ability to identify AI-related risks and implement appropriate safeguards.
• Self-driven with the ability to collaborate effectively with both business and technical teams.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Results-oriented mindset with a focus on delivering high-quality, secure, and maintainable solutions.
• Experience delivering enterprise data platform, analytics, and AI projects.
• Practical experience in Data Engineering, Platform Engineering, and AI Engineering.
• Hands-on experience with Microsoft Fabric, Azure Data Services, and AI technologies.
• Ability to translate business requirements into scalable data and AI solutions.
• Experience supporting and maintaining production AI services.
• Experience working in regulated industries, such as the financial sector, is considered a strong advantage.

Your responsibilities

• Design, build, maintain, and enhance the Microsoft Fabric data platform, ensuring its availability, performance, scalability, and reliability.
• Develop and maintain data pipelines for data ingestion, transformation, and delivery.
• Design and manage Lakehouse and Data Warehouse solutions.
• Monitor platform health, troubleshoot incidents, and ensure operational continuity.
• Design, develop, and maintain data models for reporting, analytics, and AI workloads.
• Build optimized datasets and semantic models.
• Ensure data quality through validation, error handling, and adherence to data modeling best practices.
• Design, implement, and maintain AI solutions using Microsoft AI and Azure AI services.
• Develop Generative AI solutions, Retrieval-Augmented Generation (RAG) applications, intelligent search capabilities, and AI agents.
• Prepare and manage data for AI models, including prompt engineering, model lifecycle management, and deployment.
• Collaborate with business stakeholders to identify AI use cases and continuously monitor the quality and effectiveness of AI solutions.
• Integrate source systems with the Microsoft Fabric platform.
• Design APIs and data access services for reporting, business applications, and AI solutions.
• Integrate AI services with enterprise applications while ensuring compliance with security and architectural standards.
• Leverage Azure DevOps for source code management, work item tracking, and deployment automation.
• Implement and maintain CI/CD and MLOps practices.
• Create and maintain clear, comprehensive technical documentation.
• Manage access control, auditing, and data security across the platform.
• Ensure compliance with regulatory requirements and Responsible AI principles, including AI model governance, data lineage, monitoring, and risk management.
• Translate business requirements into scalable data and AI solutions using Microsoft Fabric, Azure, and AI technologies.
• Support the onboarding of new data sources, platform automation, and continuous platform enhancement.
• Manage and prioritize the engineering backlog using Azure DevOps.
• Act as a technical expert, providing guidance and resolving complex issues related to data platforms and AI solutions.

About the project

This is how we organize our work

Benefits

• sharing the costs of sports activities
• private medical care
• remote work opportunities
• flexible working time
• integration events