Data Engineer

Reporting to a Senior Manager, you will lead the day-to-day technical execution of client projects, ensure delivery quality and coordinate small project teams. You will work directly with clients to translate business requirements into robust, scalable and well-governed data solutions. Key Responsibilities

• Leverage AI-driven code development using Github Copilot, VS Code and the Fabric MCP Server
• Own the technical delivery of data engineering workstreams, from requirements and solution design through to build, testing, deployment and documentation.
• Design and build end-to-end solutions in Microsoft Fabric, including Lakehouse, Data Pipelines, Warehouses and Notebooks.
• Develop and manage data pipelines across Bronze, Silver and Gold layers using SQL, Python and PySpark.
• Create source-to-target mappings and maintain clear data lineage, metadata and technical documentation using Fabric and Purview
• Design for schema evolution, security, workspace governance and operational support.
• Build reconciliation reporting and implement data quality controls and testing frameworks, including tools such as Great Expectations where appropriate.
• Apply Git-based version control and CI/CD practices to support reliable, repeatable deployments.
• Design dimensional data models using Kimball principles and build robust Power BI semantic models.
• Work directly with clients to clarify requirements, explain technical decisions, present progress and incorporate feedback.
• Lead small delivery teams by coordinating activities, delegating tasks, reviewing code and maintaining delivery standards.
• Identify delivery risks and technical challenges early, resolving or escalating them as appropriate.
• Contribute to pre-sales discussions, solution shaping, internal standards and knowledge sharing.

Qualifications & Experience

• A minimum of five years’ professional experience working as a Data Engineer, with responsibility for designing, building and delivering production-ready data solutions.
• Demonstrable hands-on experience delivering data engineering solutions using Microsoft Fabric. Experience with Fabric Lakehouse, Data Pipelines, Warehouses and Notebooks is required.
• Strong SQL, Python and PySpark skills for data ingestion, transformation and analysis.
• Experience developing end-to-end data pipelines and implementing medallion architecture.
• Strong knowledge of dimensional data modelling, including Kimball standards.
• Experience designing and building Power BI semantic models.
• Practical experience with Git integration, version control and CI/CD pipelines for data projects.
• Experience implementing data quality frameworks, reconciliation processes and testing methodologies.
• Ability to produce clear solution designs, source-to-target mappings and technical documentation.
• Confidence working directly with clients on requirements, technical decisions and delivery matters.
• Experience reviewing technical outputs and coordinating the work of other delivery team members.
• Excellent attention to detail, problem-solving and organisational skills.

Desirable Experience

• Experience with Databricks, Azure Synapse or other Azure data services alongside Microsoft Fabric.
• Previous consulting or client-delivery experience.
• Relevant Microsoft certifications, particularly DP-700 or DP-600. DP-203 is also valued.
• A bachelor’s or master’s degree in a relevant discipline.

Key Performance Indicators (KPIs)

• Accurate, complete and technically sound deliverables.
• Delivery against agreed milestones and project commitments.
• Positive client feedback on technical execution, communication and solution reliability.
• Client renewal and commercial growth
• High standards of code quality, governance, version control and documentation.
• Effective coordination and support of project team members.
• Continued development of Microsoft Fabric expertise and relevant certifications.
• Contribution to pre-sales activity and identification of further value for existing clients.

What we offer:

• Competitive salary.
• 25 days’ annual leave per year.
• Pension and healthcare, subject to successful completion of the probationary period.
• Dedicated learning and development days.
• Flexible working arrangements.
• Team-building days and a collaborative team culture.

For more information, please contact

Wir zeigen einen Auszug und einen Link je Anzeige, und den vollen Text, wenn die Quelle es erlaubt. Genannte Marken und Logos gehören ihren Inhabern.

Veröffentlicht am 23. Okt. 2026

Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung