About the project

• As a key step in scaling up our Supply Chain Analytics team, we are looking for a Data Engineer to drive and support data ingestion, staging, processing and serving using MS Azure services.

Your responsibilities

• Develop, optimize & maintain big data (ELT/ETL) pipelines for purposes of statistical modelling & business intelligence
• Ensure & monitor data quality and integrity
• Set up and configure data storage systems (e.g. Snowflake data lake / SQL databases)
• Manage and support production use of connections between key elements of data infrastructure
• Write and maintain secure, robust, scalable, and efficient code that turns business concepts into tangible solutions
• Drive engineering best practices like automation, CI/CD, and maintainability
• support standardization and automation by following best-practices / common development standards
• collaborate with BI analysts, data scientists, ML engineers and core IT in cross-functional teams delivering value through data solutions

Our requirements

• Broad skills in Python, SQL and bash scripting
• Min. 2-3 years of hands-on experience within Azure data components (Azure Data Factory, Blob Storage, Sharepoint, KeyVault, LogicApps, Azure DB, Synapse)
• Experience with data workflow orchestration (esp. using ADF)
• Good command of version control and CI/CD pipelines using Azure DevOps / Github
• Familiarity with data governance concepts (e.g., catalogue & meta data, data lineage, master data, security & compliance)
• Business-ready English (B2-C1)

Optional

• Experience with Snowflake will be an important asset
• Experience with Databricks, possibly also Azure ML
• Azure Data Engineer / Data Analytics certificate
• Familiarity with SAP Business Warehouse as a data source
• Understanding of BI tools, eg. Power BI
• Experience with PySpark / Scala

Technologies we use

This is how we work on a project

• Continuous Deployment

• Continuous Integration

What we offer

• B2B contract

• remote work