EU remote
Data Engineer - SCD
About this role
Supply Data & Analytics has the assignment to create value and enable business growth by bringing data from across IKEA together to gather actionable insights. Data & Analytics is passionate about making data, analytics and insights easily findable and explainable for the many to enable better and faster decision-making. We work closely with our business stakeholders and form product teams that deliver cutting edge data driven solutions for our coworkers.
We work in a modern multi cloud-based environment, and you will be a part of the engineering team continuously developing and operating data products and analytical capabilities. You will be regularly involved in workshops with coworkers to harness modern data infrastructure efficiently and provide long term solutions. Supporting a complex organisation to realise the benefits that modern data engineering can bring is at the heart of the role.
As a Data Engineer at IKEA, you will play a key role in designing, building, and maintaining our data infrastructure to support business needs, and decision-making processes. Your responsibilities will include: Design, develop, and maintain data models (including dimensional modelling, star/snowflake schemas, Data Vault, and Medallion architecture) to support business needs of analytics and self-service reporting across Core Business Supply.
Design, implement, and maintain robust ETL/ELT pipelines that integrate diverse internal and external data sources (databases, APIs, real-time streams) into IKEAs data platforms. Collaborate closely with business stakeholders, architects, analysts, data product leaders, and data scientists to translate complex supply chain and business requirements into scalable, performant, and well-governed data models and solutions.
Establish, promote, and enforce data engineering best practices, including data modelling standards, data quality, version control, testing, monitoring, documentation, and metadata management. Optimise data models and pipelines for performance, reliability, scalability, and cost-efficiency across batch and real-time processing. Ensure data is stored, processed, and accessed securely, with full adherence to data governance, privacy, and compliance standards.