Data Engineer
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("Market Average: Senior Level"), this listing's salary midpoint is about 93% lower. The offer sits below the benchmark range (€2,879–€11,033). The listed pay band (€407–€527) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 6 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Data Engineer | €3,000/per month | €5,250/per month | €7,000/per month |
| Pay in our data — not quoted in ad (Senior) | €407/per month | €467/per month | €527/per month |
Senior Data Engineer responsible for designing and building scalable data pipelines and data products powering procurement, supply chain and operations analytics. The role involves building robust data pipelines, integrating SAP and non-SAP systems, leveraging Databricks, Delta Lake, Unity Catalog and Azure, creating reusable data models across procurement, vendor, contract, logistics and operations datasets, implementing Medallion Architecture, ensuring data governance and quality, and enabling AI-ready datasets. You will collaborate with data analysts, business stakeholders and data scientists, translate complex requirements into scalable technical solutions, and adhere to engineering best practices (Git, CI/CD, automated testing). The candidate should have 4+ years in data engineering, strong Python (PySpark) and SQL skills, experience with SAP data sources, Azure, REST/SOAP integrations, and experience delivering analytics via Power BI or SAP Analytics Cloud. Proficiency in English and basic German is required, with a motivation to learn and grow. The role is hybrid based in Garching near Munich, Germany, with two days per week in the office, and is suitable for someone able to relocate if needed.
Job Details
Responsibilities
- Design scalable data pipelines
- Build data models across procurement, vendor, contract, logistics and operations datasets
- Implement Medallion Architecture for scalable analytics
- Deliver consumption-ready datasets for self-service analytics
- Ensure governance, quality and trust in data
- Develop feature-ready data products for spend analytics, supplier performance, risk management and AI use cases
- Collaborate with analysts, stakeholders and data scientists
- Assist in governance and data protection standards
- Support hybrid/AI analytics enhancements
- Contribute to engineering excellence through modern software practices
Requirements
- 4+ years of experience in data engineering or similar roles
- At least 2 years of hands-on experience with Databricks including Delta Lake, Delta Live Tables, Unity Catalog, and Workflows
- Experience with SAP data sources and enterprise applications
- Strong Python (PySpark) and SQL skills
- Experience with SAP data integration approaches (OData, CDS views, BW extraction, SAP Datasphere)
- Azure technologies experience (Azure Data Factory, ADLS Gen2, Azure DevOps)
- Experience building API-based integrations (REST and SOAP)
- Git-based development, CI/CD and automated testing
- Experience with data modelling, governance, lineage, data quality frameworks
- Experience delivering datasets and reporting (Power BI, SAP Analytics Cloud)
- Bachelor's or Master's degree in CS/IS/Engineering or equivalent
- Professional English and basic German
- Willingness to learn and grow
Skills & Technologies
Education Level
BachelorRecruitment Process
- 1CV screening
- 2Phone screening
- 3Interviews
- 4Case studies or assessments
- 5Feedback and decision
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