Data Engineer

Net2Source (N2S); Malmö kommun; On-site; SEK 600,000 - 900,000; Full time

Job summary

Net2Source (N2S) is seeking a Data Engineer to design, build, and optimize data infrastructure powering analytics, BI, and ML initiatives in a Nordic context. The role focuses on reliable data pipelines, scalable platforms, and governance-aligned practices.

You will collaborate with product and data teams to implement batch and streaming workflows, data modeling, quality checks, and observability. The ideal candidate contributes to cost efficiency, security, and documentation while aligning with

Responsibilities

• Develop and maintain data pipelines and data platform components following architectural and governance standards.
• Build scalable batch and streaming ingestion pipelines and curated datasets.
• Support data quality checks, observability tasks, and secure data handling per GDPR and metadata guidelines.
• Monitor data workloads and contribute to performance and cost improvements.
• Collaborate with product and data teams, produce clear documentation, and support knowledge transfer.

Job description

A Data Engineer is a seasoned technology professional responsible for designing, building, and optimizing the data infrastructure that powers analytics, machine-learning, and business intelligence. With deep expertise in distributed data systems, cloud platforms (GCP), and data modeling, a Data Engineer ensures that data is reliable, scalable, and accessible to technical and business teams mainly supporting Procurement BI

The Junior Data Engineer will support in developing and maintaining data pipelines and data platform components that follow architectural and governance standards. They will assist in building scalable batch and streaming ingestion pipelines, help create curated datasets, and contribute to basic data modeling. The role includes supporting data quality checks, observability tasks, and secure data handling by following GDPR, access control practices, and metadata guidelines. They will also help monitor data workloads, support performance and cost improvements, and contribute to integrations with analytics and machine-learning solutions. Collaboration with product and data teams, producing clear documentation, and participating in knowledge transfer are key parts of the role. All work should align with engineering practices, security expectations, and ways of working.