Senior Data Engineer

at  IKEA

YOUR RESPONSIBILITIES

As a Data Engineer, you will:

• Contribute to the development of D&A platform and analytical tools, ensuring easy and standardized access and sharing of data
• You will be subject matter expert for Azure Databrick, Azure Data factory and ADLS
• You will help design, build and maintain data pipelines (accelerators)
• Document and make the relevant know-how & standard available
• Ensure pipelines and consistency with relevant digital frameworks, principles, guidelines and standards
• Support in understand needs of Data Product Teams and other stakeholders
• Explore ways create better visibility on data quality and Data assets on the D&A platform
• Identify opportunities for data assets and D&A platform toolchain
• Work closely together with partners, peers and other relevant roles like data engineers, analysts or architects across IKEA as well as in your team

You will collaborate closely with Ingka Group and other functions to align, implement and develop best practices, standards and data delivery agreements.
The position will be in the Netherlands (Leiden), and you will report to the Data & Analytics Manager for Ingka Investments.

To be successful in this role, you have solid experience in data engineering, in a corporate environment. You recognise yourself in the bullet points below:

• Formal qualifications (BSc, MSc, PhD) in computer science, software engineering, informatics or equivalent
• Minimum 3 years of professional experience as a (Junior) Data Engineer
• Strong knowledge in designing efficient, robust and automated data pipelines, ETL workflows, data warehousing and Big Data processing
• Hands-on experience with Azure data services like Azure Databricks, Unity Catalog, Azure Data Lake Storage, Azure Data Factory, DBT and Power BI
• Hands-on experience with data modeling for BI & ML for performance and efficiency.
• The ability to apply such methods to solve business problems using one or more Azure Data and Analytics services in combination with building data pipelines, data streams, and system integration.
• Experience in driving new data engineering developments (e.g. apply new cutting edge data engineering methods to improve performance of data integration, use new tools to improve data quality and etc.)
• Knowledge of DevOps practices and tools including CI/CD pipelines and version control systems (e.g., Git)
• Proficiency in programming languages such as Python, SQL, PySpark and others relevant to data engineering
• Hands-on experience to deploy code artifacts into production