Data Engineer

As a Data Engineer at Monks, you will design, build, and maintain data pipelines and cloud infrastructure to support marketing analytics. You will work with cross-functional teams on data models, warehousing, and end-to-end ETL, bridging engineering with ML/Gen-AI applications. The role sits within the Data Strategy team for a major Netherlands client, in a dynamic, AI-forward environment. This is a growth-minded opportunity to deepen data engineering and data science expertise while delivering business value.

• Develop data pipelines and solutions across AWS and GCP
• Automate end-to-end ETL processes for data integration and transformation
• Design and implement data models and data warehouses
• Create data transformation recipes for warehousing-ready formats
• Document data models, architecture diagrams, schemas, and metadata
• Monitor and troubleshoot data pipelines to ensure timely data availability
• Collaborate with data science to integrate ML models and Gen-AI applications
• Demonstrate data literacy and translate technical data work into business value
• Communicate progress to technical and non-technical stakeholders
• Work independently and in teams to solve problems

• Bachelor or Masters in a quantitative field (Data Science, Computer Science, Mathematics, Statistics, or related)
• 1+ years of experience in data science or data engineering or related field
• Associate Cloud Certification (e.g., GCP Cloud Architect, Data Engineer, ML Engineer) or equivalent
• Proficiency in Python and SQL
• Experience authenticating and authorising API requests (OAuth, API keys) and troubleshooting API issues
• Strong understanding of data structures and databases
• Knowledge of data modeling tools (dbt, Dataform)
• Knowledge of data warehousing and ETL concepts with tools like Amazon Redshift or Google BigQuery
• Familiarity with data privacy principles
• Fluent English communication

• Strong analytical and problem-solving skills
• Independent and collaborative work style
• Clear communication across technical and non-technical audiences
• Python
• SQL
• Cloud platforms (AWS, GCP)