AI Data Engineer (contract)

This role is for a hands-on Data Engineer who will take full ownership of building and stabilising large-scale data pipelines using Microsoft Fabric and OneLake. The focus is on transforming fragmented, high-volume data (billions of records) into clean, reliable, and analytics-ready datasets using medallion architecture. The ideal candidate is proactive, solves data issues at the source, and ensures strong data quality, governance, and access control. They will work closely with multiple teams, design resilient pipelines, handle frequent upstream changes, and enable trusted, self-service data for business users., * Build and maintain data pipelines using Microsoft Fabric + OneLake

• Implement medallion architecture (Bronze Silver Gold)
• Develop transformations using:
• SQL / T-SQL
• Power Query / M Query
• Notebooks (Python)
• Handle very large data volumes (billions of rows) efficiently
• Identify and fix data issues at the source
• Set up:
• Data quality checks
• Monitoring & alerting
• Logging frameworks
• Build semantic models (Power BI / Fabric) for analytics
• Implement data governance + access controls (RLS, object-level, etc.)
• Collaborate with:
• Upstream system owners
• Business/data analysts
• Continuously improve pipeline reliability and scalability

• 4+ years in Data Engineering
• Hands-on experience with:
• Microsoft Fabric + OneLake
• Medallion architecture
• Strong experience in:
• SQL / T-SQL (advanced queries, optimisation)
• Data pipeline development (production-grade)
• Experience handling large-scale datasets (billions of rows)
• Strong in data transformation frameworks:
• Power Query / M Query
• Notebooks (Python preferred)
• Proven ability to:
• Troubleshoot data issues deeply
• Perform root-cause analysis
• Experience with:
• Data quality checks & validation frameworks
• Monitoring and alerting setup
• Hands-on with:
• Data governance
• Row-Level Security (RLS) / access controls
• Self-starter mindset (can work independently without direction)

Nice-to-Have Skills

• Microsoft Fabric certification
• Experience with:
• Power BI semantic modelling
• Data warehouse design (Fabric lakehouses / warehouses)
• Exposure to enterprise data governance frameworks
• Experience collaborating across multiple teams / systems

Experience Level Guidance

• 4-8 years total experience
• At least:
• 1-2 years in Microsoft Fabric ecosystem
• Background:
• Data Engineering (NOT Data Analyst heavy profiles)
• Must have worked on:
• Large-scale data environments
• Complex, messy, multi-source data systems

As a workplace, Allegis Global Solutions focuses on relationships - with each other, our clients and our candidates. In fact, serving others is one of our core values. We support open communication and recognize that giving constructive criticism can be even harder than receiving it. We appreciate the fearless and the passionate, who force us to be better. Everything we do sits on a pillar of diversity, equity and inclusion - diverse perspectives, backgrounds and ideas achieve innovation and make us successful.