Data Engineer (Power BI, Microsoft Fabric, Azure)

TL;DR

Data Engineer (Power BI, Microsoft Fabric, Azure): Designing and maintaining robust ETL/ELT pipelines and optimized data models with an accent on AI and machine learning project support. Focus on leveraging Azure and Microsoft Fabric ecosystems to ensure data quality, performance, and observability for enterprise analytics.

Location: Lisbon, Portugal (Hybrid)

Company

hirify.global is a Swiss consulting firm focused on delivering strategic, technological, and organizational transformation through innovation and professional partnership.

What you will do

• Design, build, and maintain scalable ETL/ELT pipelines for analytics and AI-driven applications.
• Develop and optimize complex data models and datasets specifically for Power BI environments.
• Implement and enforce rigorous data governance and quality standards across all production environments.
• Support cross-functional AI and machine learning teams by providing clean, well-structured features and data.
• Collaborate with data, DevOps, and observability teams to enhance data practices within Azure and Microsoft Fabric.
• Analyze production data performance to identify bottlenecks and reduce system noise.

Requirements

• 3–5 years of professional experience in Data or Analytics Engineering.
• Strong technical expertise in Power BI and advanced data modeling techniques.
• Proven ability to design and implement complex ETL/ELT data pipelines.
• Practical experience with Azure data services and proficiency in Python scripting.
• Advanced SQL skills and experience managing production-grade data environments.
• Familiarity with Microsoft Fabric, data observability tools, and CI/CD practices for data systems.

Nice to have

• Relevant Microsoft Azure or Power BI certifications.
• Experience supporting end-to-end AI/ML development life cycles.

Culture & Benefits

• Focus on career advancement and professional development opportunities.
• Supportive work environment valuing transparency, professionalism, and long-term partnerships.
• Commitment to digital innovation and social responsibility.
• Empowerment through ongoing training and skill development programs.