About Brigital

Brigital is a full-service BI, Automation & AI agency headquartered in Amsterdam. We specialize in reporting, data engineering, low code apps, automations and agentic workflows. Our goal is to help businesses harness the full power of their data and intelligent systems to discover growth opportunities, reduce costs, mitigate risks, and gain clarity.

Role Description

This is a part time (at least 10 hours / week) contractual Data Engineer (Microsoft Fabric) role with a flexible work arrangement - fully remote, with optional collaboration from Amsterdam.

You will focus on designing, building, and maintaining a parameterized data warehouse architecture within the education sector. You will work across multiple data sources, integrating databases and APIs into a scalable Fabric-based platform. The role requires strong data modeling capabilities and the ability to structure data for downstream analytics, including Power BI reporting & Copilot Agents.

You will work closely with a wider team across Europe who specialise in business intelligence AI and automation, and can grow to a full member gaining exposure to diverse projects, industries and modern data tooling.

Must Have Qualifications

At least 3 years of experience in data engineering, with hands-on experience in Microsoft Fabric or similar modern data platforms
Proven experience building and maintaining data warehouses with parameterized or modular architectures
Strong experience integrating multiple data sources, including:
Direct database connections (SQL, etc.)
API-based integrations
Experience designing and implementing scalable data models across multiple source systems
Working knowledge of Power BI (data modeling, dataset structuring, or report integration)
Strong SQL skills and understanding of data transformation logic
Comfortable working in a fully remote, contract-based environment
Confident and clear English communication skills
Located in Eastern or Southern Europe

Nice to Have

Experience with Azure Data Factory
Experience working in the education sector or similar data environments
Familiarity with data governance, data quality frameworks, and monitoring
Experience optimizing data pipelines for performance and cost efficiency
Background in a consulting or agency environment
Experience with Python
Experience with dbt

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