Lead Full Stack Data Engineer

About the Role

The Lead Full Stack Data Engineer owns Data products across the full lifecycle: from data ingestion and transformation through to semantic modelling, reporting, documentation, and user adoption. Working closely with commercial, operations, finance, and clinical stakeholders, the role translates complex and often ambiguous business requirements into clear, reliable, and scalable Analytics solutions built on Microsoft Fabric and Power BI. This position requires strong technical capability across data engineering and Analytics, a structured analytical mindset, and the ability to collaborate effectively with both technical and non-technical stakeholders. About Role 1. End-to-End BI Solution Development Design, develop, and implement full-stack Data solutions from data ingestion through to user-facing reports and apps. Take ambiguous business questions and translate them into well-defined data products, including data models, semantic layers, dashboards, and supporting documentation. Manage delivery from discovery and prototyping through validation and production support. Ensure data accuracy, integrity, and reliability across all Data solutions. 2. Data Pipelines, Modelling, and ETL Develop and maintain ingestion and transformation pipelines using Microsoft Fabric (Data Factory pipelines, dataflows Gen2, copy activities). Land, organise, and structure data using Fabric Lakehouse and/or Data Warehouse patterns. Implement layered data architectures (e.g. bronze / silver / gold) to ensure modular, reusable, and testable transformations. Set ETL/ELT standards, performance optimisation, and scalable design. Apply data quality checks, validation rules, and monitoring to proactively identify issues. Build and govern the data foundations that AI and ML depend on – clean, well-modelled, well-documented datasets and feature-ready CI/CD for the data platform (GitHub) - branching, automated testing deployment pipelines and raise the bar on engineering discipli

Key Responsibilities

• 1. End-to-End BI Solution Development
• 2. Data Pipelines, Modelling, and ETL

Requirements & Qualifications

• Strong problem solving foundations, knowledge of modern engineering practices, and interest in technology systems.

Perks & Benefits

• Official mentor support
• verified hiring timeline
• and career progression.