Data Engineer

What You'll Do

• Design, build, and maintain production data pipelines for enterprise clients across ingestion, transformation, and delivery layers
• Implement ELT/ETL workflows using Azure Data Factory, dbt, and Databricks on Azure — handling scale, performance, and reliability requirements
• Collaborate with the data architect to translate architectural designs into working, maintainable pipeline code
• Write clean, well-structured Python and SQL — code that engineers can maintain and extend after you
• Monitor pipeline health, implement alerting, and own incident response for data reliability issues
• Work directly with client data and engineering teams to understand source systems, data contracts, and downstream requirements
• Contribute to internal engineering standards, code review processes, and shared tooling

What You'll Need

• 4+ years of experience building production data pipelines in a professional engineering role
• Strong Azure data engineering experience: Azure Data Factory, Azure Data Lake Storage, Databricks, and Synapse Analytics
• Proficient in Python (PySpark and pandas) and SQL at a production level
• Hands-on experience with dbt for data transformation in a cloud lakehouse or warehouse environment
• Understanding of data modeling patterns — star schema, medallion architecture, and data vault
• Experience working in client-facing or professional services environments is a plus
• Comfort navigating ambiguity in early-stage client projects where requirements evolve

Nice to Have

• Experience with Apache Kafka or Azure Event Hubs for real-time data pipelines
• Familiarity with infrastructure-as-code tools (Terraform, Bicep) for data platform provisioning
• Tableau or Power BI development experience
• AWS or GCP data engineering background
• Data quality tooling (Great Expectations, dbt tests, Soda)

What We Offer

Ready to apply?

Send your CV and work samples to hello@dataarchitect.co with subject line: Data Engineer Application