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

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Posted Oct 23, 2026

Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation