Enterprise Data Architect Azure & Fabric Platform Lead

Adastra Resource Group

United States

Remote

USD 110,000 - 190,000

Full time

9 days ago
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Job summary

Adastra Resource Group is seeking a Data Architect to design scalable data models and build end-to-end data pipelines in a remote, direct-hire role. You will work with enterprise teams across Finance, Sales, Operations, and Supply Chain to enable decision-making through robust analytics on Azure.

You'll contribute to a Microsoft Fabric platform initiative, leveraging Azure Synapse Analytics, Data Lake Gen2, and Power BI to deliver trusted data assets and insights while maintaining data quality

Qualifications

  • Hands-on experience in data engineering, analytics engineering, or BI.
  • Strong SQL and relational database/dWH understanding.
  • Experience building or supporting ETL/ELT pipelines and enterprise reporting datasets.
  • Knowledge of data lakes, cloud analytics architectures, APIs, and data-quality practices.
  • Familiarity with Power BI and data visualization.

Responsibilities

  • Design and develop dimensional models, fact tables, and data products for enterprise reporting.
  • Build and maintain ETL/ELT pipelines across ERP, finance, sales, operations, and supply chain systems.
  • Write, optimize, and support SQL code, stored procedures, and data-quality checks.

Skills

SQL
Data warehousing
Dimensional modeling
ETL/ELT pipelines
Cloud analytics
Power BI
Python/PySpark

Tools

Azure Synapse Analytics
Data Factory
Azure SQL Database
Data Lake Storage Gen2
GitHub Copilot

Job description

Adastra Resource Group is seeking a Data Architect to design scalable data models and build end-to-end data pipelines in a remote, direct-hire role. You will work with enterprise teams across Finance, Sales, Operations, and Supply Chain to enable decision-making through robust analytics on Azure.

You'll contribute to a Microsoft Fabric platform initiative, leveraging Azure Synapse Analytics, Data Lake Gen2, and Power BI to deliver trusted data assets and insights while maintaining data quality

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