Analytics Engineer

At Interfood, data is a key driver for our business. As an Analytics Engineer at our global Global Headquarters in Eindhoven, you'll own business-facing data products from requirements to production. Working closely with business stakeholders, you'll translate business needs into trusted, analytics-ready datasets, combining strong business understanding with hands-on technical delivery using SQL, Python and modern Azure technologies.

You'll become part of our Global Data & Analytics team: an ambitious and collaborative team where innovation, ownership and continuous improvement are part of everyday work. In this role, you'll collaborate with colleagues across the business, translate business needs into trusted data solutions and contribute to solutions that create real value for our international organization, all while continuing to grow your technical expertise.

As an Analytics Engineer you: 

• Own data products end-to-end by gathering business requirements, managing stakeholders, prioritizing work, and delivering trusted analytics solutions from design through production support.
• Develop and maintain data pipelines by building batch data ingestions and transforming raw data into analytics-ready datasets using SQL and Python (and dbt where applicable). 
• Support and continuously improve existing data products by monitoring, troubleshooting and resolving production issues, and enhancing the reliability and performance of ingestion and transformation processes.
• Apply data governance practices by implementing data quality checks, metadata, lineage and business definitions to ensure trusted and well-governed data products.
• Collaborate with business stakeholders to understand their needs and translate them into practical, analytics-ready data solutions.
• Deliver reliable, high-quality data products that enable data-driven decision-making.
• Build trusted relationships with business stakeholders and successfully manage expectations, priorities, and dependencies.
• Ensure production data products remain reliable, maintainable, and aligned with evolving business needs. 
• Contribute to engineering standards, knowledge sharing, and continuous improvement within the team.

Nice to have

• Hands-on experience with dbt, Databricks, and Apache Spark.
• Experience applying data quality, metadata management, and data governance best practices.