Senior Data Engineer (Python / Azure)

DCG is an organization that connects business needs with people's ambitions, helping candidates find suitable work environments and companies build effective teams. They focus on close collaboration by listening and responding carefully to important aspects for individuals and organizations, creating lasting and valuable relationships.

• 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 comprehensive data structures
• Strong proficiency in Python for production ETL/ELT and working knowledge of SQL
• Experience with REST API integrations including authorization, pagination, query limits, retries, and JSON/XML parsing
• Practical knowledge of data quality assurance, schema drift handling, and data reprocessing
• Experience with Azure services: Azure Data Lake Storage, Azure Data Factory, Azure Functions, Azure SQL, Azure Databricks or Microsoft Fabric
• Familiarity with Git and CI/CD processes in Azure DevOps or GitHub Actions
• Experience documenting solutions and delivering them for maintenance by external teams
• English proficiency at minimum B2+ level, enabling independent direct collaboration with clients

Nice to have:

• Knowledge of Infrastructure as Code tools such as Terraform or Bicep
• Experience designing data models for Power BI
• Exposure to legislative or regulatory data sources, e.g., Congress.gov or UK Parliament APIs

• Design data warehouse or lakehouse architectures tailored to client environments and requirements
• Implement bronze, silver, and gold layers within the medallion architecture
• Develop dimensional models including fact and dimension tables using the star schema
• Analyze client business taxonomy and identify areas needing refinement
• Translate taxonomy into data dictionaries, classification structures, and data models
• Build production ETL/ELT pipelines using Python integrating regulatory and parliamentary data sources
• Develop validation mechanisms, schema drift handling, logging, error handling, and data reprocessing capabilities
• Collaborate with clients to clarify requirements and make technical decisions
• Prepare architecture documentation, data models, and ETL pipeline descriptions for client teams