Senior Data Engineer (Python / Azure)

DCG is a company offering a remote position for a Senior Data Engineer working with Python and Azure technologies, focusing on data engineering projects including building data warehouses and lakehouses for clients.

• Minimum 5 years of commercial experience in data engineering
• Experience designing and building data warehouses or lakehouses from scratch
• Practical knowledge of dimensional modeling, star schema, and medallion architecture
• Ability to translate business taxonomy into data structures and assess completeness and consistency
• Strong production-level proficiency in Python for ETL/ELT and good knowledge of SQL
• Experience with REST API integrations including authorization, pagination, request limits, retries, and JSON/XML parsing
• Practical knowledge of data quality mechanisms, schema drift handling, and data reprocessing
• Experience with Azure Data Lake Storage, Azure Data Factory, Azure Functions, Azure SQL, Azure Databricks, or Microsoft Fabric
• Familiarity with Git and CI/CD processes using Azure DevOps or GitHub Actions
• Experience documenting solutions and transferring them to maintenance teams
• English proficiency at minimum B2+ level and ability to work independently with clients

• Design and build data warehouses or lakehouses considering client environment and requirements
• Implement bronze, silver, and gold layers within medallion architecture
• Develop dimensional models including fact tables, dimensions, and star schema relationships
• Analyze business taxonomy maturity and identify areas needing clarification
• Translate business taxonomy into data dictionaries, classification structures, and data models
• Build production-grade ETL/ELT pipelines using Python integrating with regulatory and parliamentary data sources
• Design and implement validation mechanisms, schema drift handling, logging, error handling, and data reprocessing
• Collaborate with clients for requirement clarification and technical decisions
• Prepare architecture, data model, and pipeline documentation and hand over to client teams