Data Engineer (Azure Data Factory)

Addepto is a leading AI consulting and data engineering company that builds scalable, ROI-focused AI solutions for large enterprises and startups. It focuses exclusively on Artificial Intelligence and Big Data, helping organizations unlock the potential of their data through systems designed for measurable business impact and long-term growth. Addepto is part of KMS Technology, a US-based global technology group, combining AI specialization with enterprise-scale delivery capabilities.

• Strong hands-on experience with Azure Data Factory including pipeline and orchestration design, linked services, datasets, triggers, parameterization, operational monitoring, troubleshooting, performance tuning, and deployment-aware development in enterprise environments.
• Excellent knowledge of Python (Azure Functions, REST APIs, automation).
• Strong SQL skills and solid understanding of data modeling for ETL/ELT and warehouse workloads.
• Experience with CI/CD processes in Azure DevOps (pipelines, releases, multi-environment deployments).
• Solid understanding of Azure services and cloud-based data solutions (e.g., Azure SQL Database, Azure Key Vault).
• Experience with Power BI for occasional dashboarding and reporting.
• Experience working with modern development practices and tools.
• Consulting mindset with proactive communication and strong stakeholder alignment skills.
• Ability to collaborate effectively with Product Owner and Architect during planning and delivery.
• Independent and responsible approach to delivering high-quality solutions.
• Excellent command of English (at least C1 level).

Nice to have:

• Knowledge of dbt.
• Experience implementing data warehouses on Azure.

• Design, develop, and maintain Azure Data Factory pipelines, including orchestration, parameterization, and trigger management.
• Configure and manage linked services and datasets within Azure Data Factory.
• Monitor, troubleshoot, and optimize Azure Data Factory pipelines to ensure performance and reliability.
• Develop and maintain ETL/ELT processes and support the evolution of the data warehouse layer (Azure SQL Database or Synapse).
• Translate business requirements into technical solutions in close collaboration with the Product Owner and Architect.
• Develop and maintain Python-based components such as Azure Functions, API integrations, and automation scripts.
• Contribute to CI/CD processes in Azure DevOps, including pipelines, releases, and environment promotion.
• Support occasional Power BI reporting and dashboarding needs.
• Ensure proactive communication, stakeholder alignment, and visibility of risks and impacts.
• Take ownership of assigned tasks and actively contribute to continuous platform improvement.