Data Engineer

WE Fashion is in the middle of a large-scale business and IT transformation, in which data plays an increasingly important role in decision-making. As a Data Engineer, you lay the foundation for our data-driven way of working. You play a crucial role in building a robust, scalable and efficient data infrastructure that enables the organization to turn data into reliable insights. You don’t just build data pipelines and platform components; you also actively think along about how data scientists, analysts and business users can work with data in the most effective way. In this role, you ensure that data is of high quality, readily available and scalable, enabling analyses and models to be developed and applied effectively across the organization.

You work closely with data architects, data scientists, analysts and business stakeholders, advising on technical data solutions and translating raw data into a solid and reliable data foundation.

 What you will be responsible for

• Designing, building and maintaining robust and scalable data pipelines for data ingestion, validation, storage and transformation.
• Building a reliable data infrastructure that forms the foundation for data-driven decision-making within WE Fashion.
• Integrating multiple internal and external data sources into a consistent and high-quality data foundation.
• Ensuring that data is optimally available and usable for data scientists, analysts and business users.
• Actively contributing ideas on how data can best be exposed and utilized, enabling analyses, dashboards and models to be developed and applied effectively.
• Developing, managing, and optimizing the Data & Analytics Platform and the underlying data ecosystem.
• Monitoring and improving the performance, scalability and reliability of data solutions.
• Collaborating with data architects on data quality, governance and standards within the data domain.
• Resolving incidents, managing capacity and ensuring platform continuity.
• Identifying improvement and optimization opportunities and contributing to innovation within the data engineering domain.
• Creating and maintaining clear documentation for data pipelines, architectures and data processes.

You will report to the Platform Lead and work within a multidisciplinary platform team that combines technology, data, and business. In this position, you will operate in a dynamic project context at the intersection of development and operations.  You will start hands-on with analytics & reporting support and develop further in the areas of backend, data platform, and architecture.

What we expect from you:

• A completed Bachelor’s or Master’s degree in IT, Computer Science, Data Engineering or a comparable field.
• At least 5 years of experience as a Data Engineer or in a similar data-driven role.
• Experience building and maintaining data pipelines and working with ETL/ELT processes.
• Knowledge of SQL and/or NoSQL, data modelling and big data technologies.
• Experience with cloud-based data platforms and modern data architectures.
• Familiarity with data governance, data quality and security within the data domain.
• An analytical, accurate and problem-solving mindset, with a proactive and collaborative attitude.

 All applicants are evaluated based on competencies, experience and equal pay m/f/x.

With your expertise in data engineering, you ensure that WE Fashion can rely on trustworthy data and continue to make data-driven decisions. Naturally, we offer something in return.

• A salary that matches your knowledge, education and experience.
• A laptop and phone to support hybrid working.
• Travel allowance, 25 vacation days, 8% holiday allowance (paid monthly or annually), standard 20% staff discount, pension plan and comprehensive collective insurances.
• Annual “Moments that Matter Day” – an extra day off for something meaningful to you.
• Continuous learning and development opportunities through the WE® Academy.
• Discount on sports subscriptions, bootcamp or boxing classes, free fruit at our head office and plenty of team events.