Data Engineer

We are now looking for a Data Engineer on the behalf of our client. Scope of Work: Join us in shaping the future of a data-driven IKEA! The Retail Concept Operations (RCO) capability area is establishing digital products that provide performance insights for both Customer Meeting Points (CMPs) and IKEA Franchisees. These products aim to consolidate data from multiple business systems into trusted, scalable, and automated data products that support performance management, business decision-making, continuous improvement, and strategic planning. The initiatives require a robust data engineering capability to create the underlying data foundation that enables reporting, analytics, governance, and future scalability. As a data engineer in the team you will design, build, and maintain automated, scalable data solutions supporting the CMP Performance Evaluation and Franchisee Performance Evaluation products, stretching across all IKEA franchisees, transforming today’s manual, fragmented reporting into a reliable and centralized analytics ecosystem. Your work will focus on connecting data from multiple sources to deliver a unified performance evaluation framework that covers multiple criteria. You will need to ensure accuracy, data validation, version control, and auditability, enabling leadership and management teams to access consistent, trustworthy metrics for trends analysis and continuous improvement. As a Data Engineer you will play a key role in developing CMP and Franchisee Performance Evaluations We expect candidates to: Comfortable working in the early phases of solution design and contributing throughout the full data engineering lifecycle, including ideation, high level and low level architecture, requirements specification, functional and technical design, estimation, sprint planning, development, testing, documentation, deployment, and operational follow up. Strong understanding of data engineering guidelines, release processes, and quality expectations, including data validation, performance optimization, monitoring, and troubleshooting in production environments. Passionate about building clean, scalable, resilient, and cost efficient data solutions using cloud native architectures and modern data platforms, with a strong focus on maintainability and reusability. Proven experience designing and implementing end to end data pipelines (batch and streaming), including ingestion, transformation, and serving layers, using best practices in data modelling and lakehouse architecture. Hands on expertise with Databricks , including Apache Spark, Delta Lake, job orchestration, performance tuning, and environment management. Strong knowledge of Microsoft Azure , particularly services commonly used in data platforms such as Azure Data Lake Storage ,etc Solid experience with DevOps practices , including source control (e.g., Git), CI/CD pipelines, automated testing, environment promotion, and infrastructure as code for data platforms. Strong communication skills, with the ability to clearly explain data architectures, pipelines, and trade offs to non technical stakeholders. You will work with: Databricks (Apache Spark, Delta Lake, notebooks, job orchestration, performance optimization) Microsoft Azure (e.g., Azure Data Lake Storage) DevOps & CI/CD (version control, automated testing, deployment pipelines, infrastructure as code) Start: 2026-11-01 Duration: 2027-11-01 (possibility for extension) Workload: 100% Location: Malmö We will present candidates on an ongoing basis, so if interested please don´t hesitate to apply!