Data Engineer (Azure / Python / ETL) - Remote

• Minimum 3 years of professional experience in Data Engineering or a similar role
• Strong hands-on experience with Python development for production data solutions
• Solid knowledge of SQL and data processing concepts
• Practical experience with Azure data services (2–3+ years), including technologies such as Azure Data Factory, Azure Blob Storage, Azure SQL Database, Azure Synapse, Azure Key Vault, Logic Apps, SharePoint integrations
• Experience building and maintaining ETL/ELT pipelines
• Experience with workflow orchestration, especially Azure Data Factory
• Experience with Databricks and/or Snowflake
• Good understanding of CI/CD practices and version control using Azure DevOps or GitHub
• Knowledge of data governance concepts, including metadata, data lineage, security, compliance, and master data management
• Business-level English skills (B2–C1)

Optional

• Azure Data Engineer or Data Analytics certification
• Experience with PySpark and/or Scala
• Understanding of BI tools, including Power BI
• Experience working in analytics or supply chain-related environments

Support the development of modern data solutions within a large-scale Azure environment
Build and maintain reliable data pipelines, ensuring high-quality data processing and enabling advanced analytics and business intelligence solutions
Focus strongly on Python-based data engineering, with less emphasis on reporting development ,[Develop, optimize, and maintain big data ELT/ETL pipelines supporting statistical modelling and business intelligence solutions, Design and implement robust data ingestion, staging, processing, and serving workflows using Microsoft Azure services, Ensure data quality, integrity, monitoring, and reliability across data solutions, Configure and maintain data storage solutions, including Snowflake data lake and SQL databases, Build and support production-grade integrations between key components of the data infrastructure, Write secure, scalable, and maintainable Python code that transforms business requirements into technical solutions, Apply engineering best practices, including automation, CI/CD, version control, and code quality standards, Collaborate with BI Analysts, Data Scientists, ML Engineers, and IT teams to deliver valuable data-driven solutions] Requirements: Python, SQL, Azure, Databricks, Snowflake, Azure Data Factory, PySpark, Scala, Power BI Additionally: Sport subscription, Private healthcare.