Job Title: Data Engineer
Location: Warrenville, IL (Hybrid)
1st round: Assessment test on Python, SQL and Fabric
2nd round: Client interview
This is a standard enterprise-grade Data & Analytics Engineer role with a heavy focus on the Microsoft Cloud Stack.
The ideal candidate manages the entire data lifecycle from raw ingestion to end-user semantic modeling in Power BI.
Core Technical Pillars:
Medallion Architecture & Storage: Architecting Bronze (raw), Silver (cleansed/conformed), and Gold (aggregated star schema) layers using Delta Lake on Microsoft Fabric (OneLake) or Azure Databricks (ADLS Gen2).
Pipeline Development: Building ETL/ELT pipelines with PySpark, SQL, and Microsoft Fabric Data Factory / Notebooks.
Hybrid BI Capabilities: Developing enterprise-grade Power BI semantic models (leveraging Direct Lake mode) and writing complex DAX measures.
DevOps & Governance: Implementing CI/CD pipelines for data workloads and Power BI assets, setting engineering standards, and writing technical documentation.
Key Skills Matrix
Focus Area | Core Technologies & Concepts |
Languages | Python, PySpark, SQL (T-SQL), DAX |
Compute & Storage | Microsoft Fabric (OneLake, Data Factory, Lakehouse), Azure Databricks, ADLS Gen2, Delta Lake |
Data Modeling | Kimball Dimensional Modeling, Star Schema, Fact Tables, Dimension Tables, Medallion Architecture |
BI & Analytics | Power BI, Semantic Models (Direct Lake, Import, DirectQuery), DAX Measures |
DevOps & Practices | Azure DevOps, GitHub Actions, Fabric Git Integration, CI/CD Pipelines |
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