The posting, in Enpal's own words
archived Sep 9, 2026About the role
We are looking for a (Senior) Analytics Engineer to join our team. In this role, you will work closely with stakeholders across ERP, Supply Chain Management, Logistics to turn complex business questions into clear, reliable and actionable data solutions. You will take ownership of analytics projects from initial requirements through data modelling and delivery. The role combines stakeholder management, business analysis, hands-on analytics and modern data engineering, with an advanced Agentic AI toolkit at hand to help you deliver high-quality data products efficiently. Your responsibilities Partner with business stakeholders to understand their objectives, processes and analytical needs. Translate business requirements into scalable data models and analytical solutions. Take end-to-end ownership of analytics projects, including scoping, prioritisation, delivery and stakeholder communication. Build and maintain reliable data models and transformations using SQL and dbt. Design and develop scalable, business-ready data models that provide a trusted foundation for decision-making. Ensure data quality, consistency and transparency across analytical products. Own new data integrations in the ERP and SCM domain, working closely with data engineers and business teams from source onboarding through production. Identify opportunities to simplify or automate recurring reporting and operational workflows. Leverage Agentic AI and LLM-based tools to deliver high-quality data products efficiently. Communicate progress, risks, dependencies and recommendations clearly to both technical and non-technical audiences. Contribute to analytics standards, documentation and knowledge sharing across the team. What you bring 5+ years of experience in business intelligence, analytics, analytics engineering, data engineering or a comparable role. A good understanding of data modelling, data quality and analytical best practices. Practical experience with data engineering concepts, including data pipelines, transformations, SQL/dbt and cloud data platforms. Experience working with modern data warehouses such as Snowflake, BigQuery, Redshift or similar. Knowledge of or hands-on experience with ERP systems such as Microsoft Dynamics 365 or SAP, including their business processes and underlying data. The ability to understand business processes and translate them into effective data solutions. Strong stakeholder-management and communication skills. A structured, proactive and ownership-driven way of working.