> Markdown version of [/jobs/ext/3809797-lead-data-engineer](https://www.wearedevelopers.com/jobs/ext/3809797-lead-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Lead Data Engineer

- **Company:** 17918
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £38,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Application Integration Architecture, JIRA, Microsoft Azure, Business Systems, Software as a Service, Cloud Computing, Cyber Security, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Executive Information Systems, Design of User Interfaces, Infrastructure as a Service (IaaS), Meta-Data Management, Platform as a Service (PAAS), Power BI, SAP (Applications), Data Streaming, Systems Integration, Tableau (Software), Technical Data Management Systems, Value Engineering, Private Cloud Environment, Data Storage Technologies, Data Ingestion, Multi-Cloud, Microsoft Fabric, Data Lakes, Real Time Data, Operational Systems, Data Objects, Front End Software Development, Drift Detection, Data Pipelines
- **Published:** October 18, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/lead-data-engineer/52602401

## About the Role

non-technical senior leaders, Complex System Design: Applying design skills to environments where data is highly fragmented across different business units. Role specific knowledge and experience Minimum / essential Advanced proficiency in Power BI and/or Microsoft Fabric to create professional grade executive dashboards. Experience in data modelling, metadata management, design, coding, testing and delivery of data engineering solutions. Experience in supporting large change projects / programmes covering digital transformation and multiple technology architecture domais. Experience with ETL tools, scripts, and data storage methods (Data Warehousing / Data Lakes) used for performance analytics. Experience with cloud technologies such as SaaS, IaaS, PaaS etc. and / or multi cloud infrastructure and network capabilities (Azure, AWS, public / private cloud, etc). Experience in Cyber Security best practices and regulations. Professional Qualification and Certification Microsoft certified
Data Engineer Desirable Experience in a VMO, PMO, or Strategy-led data function. Background in financial modelling or commercial performance analytics. Microsoft Certified: Fabric Analytics Engineer Associate or Power BI Data Analyst Associate Line management experience. Main accountabilities Automated Value Pipeline: Design and implement complex data flows that connect operational systems (e.g., Jira, Azure DevOps), financial systems (e.g., SAP) and other systems to automate benefit tracking. Executive Dashboarding: Build and maintain high-fidelity interactive dashboards (Power BI/Tableau) that visualize OKRs, KPIs, and actual vs. forecasted ROI. Integration Architecture: Apply knowledge of systems integration to create a "Single Source of Truth" for portfolio prioritization and resource allocation. Value-Drift Monitoring: Engineering automated alerts and reporting systems that flag when an initiative's value case begins to erode based on real-time data. Stakeholder Collaboration

## Description

Data Engineering Lead required by our client an international educational establishment to provide the technical engine for the Value Management Office automating the visibility of portfolio performance and benefit realization across the organization. It is responsible for building and maintaining the "Value Dashboard," ensuring that data from disparate systems (Finance, Project Management, and Operations) is integrated to provide a real-time view of strategic ROI. The role holder defines technical standards for value-tracking tools and creates automated data objects that link project outputs to the organisation's strategic objectives. Role specific skills Full-Stack Analytics Engineering: Mastery of the lifecycle from data ingestion (ETL/ELT) to front-end visualization. Business Systems Analysis: Ability to map technical project metadata to financial value metrics. Stakeholder Communication: Experience in translating technical data structures into presentable, intuitive interfaces for