Data Engineer

Data Engineer – Azure Data Platform

Location: Limburg

Employment type: Permanent / Payroll

Working model: Hybrid – approximately 3 days per week on-site

Are you a hands-on Data Engineer who enjoys building reliable data pipelines, solving data-quality issues and improving the foundations behind analytics and reporting?

We are looking for a Data Engineer to join a small, experienced data team and help further develop and maintain an Azure-based data platform. You will work with a broad range of data, including production, finance, time-series and SAP data, and play an important role in ensuring that high-quality data is available for reporting and analytics.

This is a practical engineering role with plenty of ownership. You will work on both new development and the optimisation of existing solutions, while also having the opportunity to explore technologies such as Microsoft Fabric as the data platform continues to evolve.

What you will do

• Build, maintain and optimise data pipelines within an Azure-based data environment.
• Develop scalable SQL transformations and implement new business logic.
• Integrate new data sources, including production, finance, time-series and SAP data.
• Monitor and troubleshoot existing pipelines, investigating issues such as missing data, duplicate records, failed loads or unexpected source files.
• Design and improve data models for BI and reporting, using dimensional modelling principles such as Kimball where appropriate.
• Create reliable, accessible datasets for Power BI and other reporting solutions.
• Work closely with data analysts and reporting specialists to translate reporting requirements into robust data solutions.
• Improve data quality, reliability, performance and maintainability across the platform.
• Investigate underlying platform components and infrastructure when required rather than treating the platform as a black box.
• Contribute to the evaluation and adoption of technologies such as Microsoft Fabric, Azure Synapse and other modern data-platform capabilities.
• Take increasing ownership of the internal data platform and contribute ideas on how it can be improved over time.

What we are looking for

• Solid professional experience in data engineering.
• Strong SQL skills and practical experience building and troubleshooting data pipelines.
• Experience working with Microsoft Azure data technologies.
• Familiarity with tools such as Azure Data Factory, Azure Synapse Analytics and Azure Data Lake.
• Good understanding of data modelling, dimensional modelling and schema design.
• Ability to analyse existing data solutions and identify opportunities for improvement.
• A pragmatic, hands-on mindset: you enjoy investigating issues and understanding how systems work under the hood.
• Interest in learning or further developing your knowledge of Microsoft Fabric and related Microsoft data technologies.
• Strong collaboration skills and the ability to work effectively within a small technical team.
• Professional fluency in English.

Experience with SAP data, manufacturing or production data, finance data or time-series datasets is considered a strong advantage. Knowledge of Dutch is beneficial for day-to-day communication, but is not a requirement.

What you can expect

You will join a compact data team where your contribution is visible and where you can take genuine ownership of the data platform. Rather than working purely on isolated projects, you will help build long-term internal knowledge and continuity.

You can also expect:

• A permanent employment contract.
• A competitive salary package.
• Company car.
• Meal vouchers.
• Laptop and mobile phone with telecom subscription.
• Comprehensive group insurance.
• 32 days of annual leave.
• Hybrid working, with an intended presence of approximately three days per week
• Access to external platform specialists when additional expertise is required.
• The opportunity to help shape the future direction of the organisation's Microsoft data platform.

If you enjoy combining SQL, Azure, data pipelines and data modelling with practical problem-solving and ownership, this could be an excellent next step.