Vacant job

Do you want to work in a role where you actually make a difference, where your ideas are valued, and where you get to help build a modern analytics data platform from the ground up? The Credit Function at PayEx is now looking for a driven and solution-oriented Data Engineer who wants to modernize their analytical capabilities and take their data flows to the next level.

About the role

The Credit Function at PayEx is responsible for overall quality-assured credit risk management. The team currently consists of five people: two analysts, two Data Engineers, and your future manager, Johan – and this is where you will join as the sixth team member!

About two years ago, the journey to build PayEx's analytics data platform from scratch began. They have recently migrated from an on-premise environment to Azure and are now developing their platform in Fabric with a modern architecture. PayEx is continuously launching new products, which places exciting demands on new adaptations in their systems. This is not a role where you just "write code". You will understand the business needs, talk to internal stakeholders, design how data should be structured, and hold the entire area together.

What we offer

• You are offered a role with significant autonomy where you get to work with modern technology such as Microsoft Fabric and dbt. We offer a dynamic work environment in a driven team where you have great opportunities to influence our technical architecture and development.
• A fixed-term position via Academic Work with a fixed monthly salary. There are good opportunities for permanent recruitment to PayEx for the right candidate!

Responsibilities

The role entails overall responsibility for transforming raw data into valuable insights through modern technology and architecture in a cloud-based environment, with a focus on optimizing data warehouses and flows.

• Build and design: Develop and maintain robust ELT pipelines to collect, transform, and load data from various sources, as well as optimize data warehouses.
• Architecture: Further develop and manage our modern data platform in Fabric as well as our medallion architecture to ensure high availability, performance, and security.
• Data modeling: Design and build models that support advanced analysis and reporting, and ensure that data is well-structured.
• Collaboration & Requirements gathering: Work closely with analysts and other stakeholders to understand their data needs and translate these into technical solutions.
• Documentation & Development: Document processes and technical solutions and explore new technologies and tools. We use modern frameworks such as DBT for SQL code, Python, and GitHub Copilot to streamline our work.

We are looking for you who

• Have a relevant academic education in systems science or software engineering
• Have advanced knowledge of SQL, Git, and Python
• Have experience working with DBT and ELT processes
• Have good knowledge of data modeling and warehouse solutions
• Have experience with cloud platforms such as Fabric or equivalent
• Have very good skills in Swedish and English, both spoken and written

It is an advantage if you have

• Experience from banking, finance, or the credit market
• Knowledge of Power BI or other visualization tools

To succeed in the role, you have the following personal qualities:

• Goal-oriented
• Social
• Organized
• Responsible
• Energetic

Our recruitment process

This recruitment process is handled by Academic Work, and our client's request is that all questions regarding the position are sent to Academic Work.

We apply continuous selection and will remove the ad when enough candidates have reached the final stage of the recruitment process. A CV is requested when applying. We do not use a cover letter as a selection method, so one does not need to be attached. The recruitment process includes two selection tests: a personality test and a cognitive ability test. The tests are a tool to find the candidate with the highest potential for the position and to promote equality, diversity, and a fair recruitment process.