Data Engineer (Production & Supply Chain)

Quick Facts

• Role: Data Engineer – Production & Supply Chain

• Focus: ETL/ELT pipelines and production/supply chain data products for BI, analytics, machine learning, and AI

• Reporting: Data & Analytics Platform Architect

Description

Turn operational data into reliable, scalable data products that enable reporting (including Power BI), machine learning, and AI use cases across production and supply chain. You will integrate data from ERP, MES, WMS, planning, transport, and quality systems, and build trusted datasets with strong data quality, lineage, monitoring, and observability. Collaborate with BI/RT partners, data scientists, IT, and business stakeholders to deliver actionable insights for planning, inventory, logistics, service, and quality.

Responsibilities

• Develop, maintain, and optimize robust ETL/ELT pipelines for trusted datasets

• Integrate operational data from production and supply chain systems (ERP, MES, WMS, planning, transport, quality management)

• Design and manage data products and semantic models for use cases such as production performance, forecasting, inventory management, OTIF, planning, traceability, logistics costs, and operational efficiency

• Ensure data quality, monitoring, documentation, lineage, and observability

• Apply modern engineering practices: version control, CI/CD, testing, DataOps, and data modelling standards

• Translate business needs into scalable data solutions with data scientists, BI professionals, IT, and stakeholders

Requirements

• Master’s degree in Data, IT, Engineering, or related field

• 3–6 years of experience as a Data Engineer/Analytics Engineer or similar

• Fluency in English and Czech

• Strong SQL and Python

• Experience with cloud data platforms (preferably Azure and/or Databricks/lakehouse)

• Experience with data modelling, ETL/ELT, data warehouses, lakehouse architectures, testing, and documentation (dbt is a plus)

• Understanding of data quality, governance, security, observability, and performance

• Strong analytical and communication skills; pragmatic, collaborative mindset

• Experience leveraging AI tools to improve productivity and collaboration

• Strong advantage: SAP ERP experience and related business processes

Benefits

• Attractive compensation with annual bonus (and company car for senior candidates)

• Work with a growing Data & Analytics organization building a modern data platform, with training and certification opportunities

• High-impact projects for international production performance (e.g., energy efficiency, product quality, line capacity, planning, sustainability)

• Chance to shape digital transformation in a complex food production domain with suppliers, startups, and academic partners

• Support for wellbeing via sports and team events

• Career growth through the LLBG Academy and a dynamic, initiative-friendly environment