Requirements

Expected technologies

Python

SQL

MDX

Bash

Microsoft Azure

Optional technologies

Airflow

Azure DevOps

Snowflake

SAP

Microsoft Power BI

PySpark

Scala

Our requirements

• At least 3 years of commercial experience working as a Data Engineer/similar role
• Proficiency in Python, SQL, MDX, and bash scripting
• At least 2 years of hands-on experience with Azure data services (Data Factory, Synapse, Data Lake, Blob Storage, SharePoint, Databricks)
• Experience with data workflow orchestration (ADF, Databricks Jobs; Airflow is a plus)
• Familiarity with version control and CI/CD pipelines (preferably Azure DevOps)
• Very good English - at least B2+

Optional

• Knowledge of Snowflake within Azure environments
• Experience with SAP Business Warehouse as a data source
• Relevant certifications (Azure Data Engineer, Data Analytics)
• Knowledge of BI tools such as Power BI
• Familiarity with PySpark or Scala

Your responsibilities

• Design, build, and maintain efficient ELT/ETL pipelines for statistical models and BI applications
• Monitor and ensure data quality, consistency, and integrity
• Set up and manage data storage solutions (SQL databases, Data Lake)
• Maintain and optimize data infrastructure integrations
• Write secure, scalable, and maintainable code that brings business requirements to life
• Apply best engineering practices, including automation, CI/CD, and maintainability standards
• Collaborate closely with BI analysts, data scientists, ML engineers, and IT teams on end-to-end data projects