Data Engineer (Azure / Python / ETL) – Remote

Square One Resources is looking for a Data Engineer to support the development of modern data solutions within a large-scale Azure environment.

• 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 Azure Data Factory, Azure Blob Storage, Azure SQL Database, Azure Synapse, Azure Key Vault, Logic Apps, and 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)

Nice to have:

• 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

• 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