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# Senior Data Engineer (Microsoft Fabric / Azure)

- **Company:** Forte Grp, Inc
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Microsoft Azure, Code Review, Databases, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Dimensional Modeling, Github, Python (Programming Language), Microsoft Data Access Components, Microsoft Software, SQL Azure, Performance Tuning, Power BI, Azure Data Lake, SQL Stored Procedures, SQL Databases, Transact-SQL, Parquet, Azure Data Factory, Apache Spark, Indexer, Git, Build Management, Microsoft Fabric, Pyspark, Software Version Control, Data Pipelines, Service Stack, Databricks
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-microsoft-fabric-azure-atlanta-ga--25febda9-37d7-4eb1-b687-e951b1dc8e36

## About the Role

Microsoft Windows Azure, Sun ONE Studio, Data Warehousing, Database Extract Transform and Load (ETL), Data Modeling, SQL (Structured Query Language), Data Analysis, Microsoft Windows Azure, Microsoft Product Family, Technical Leadership, * 4+ years of data engineering experience, with at least 2 years on the Microsoft data stack

 * Hands-on experience with Microsoft Fabric (or strong Synapse / ADF background with clear path to Fabric)
 * Hands-on experience implementing Medallion Architecture (Bronze / Silver / Gold) end-to-end on the Microsoft stack
 * Solid Azure SQL and T-SQL fundamentals - you can read an execution plan and reason about performance
 * Strong written and spoken English - comfortable in client-facing conversations and async written collaboration
 * Proactive and self-directed - able to take an ambiguous problem, scope it, and drive it to a working solution
 * Strong communication, leadership presence, and collaboration skills

Nice to Have

 * Experience with Power BI semantic models, DAX, and report performance tuning
 * Familiarity with data governance, lineage, and cataloging (Microsoft Purview)
 * Exposure to Databricks or other Spark-based platforms
 * Domain experience in enterprise data warehousing for U.S. clients
 * Microsoft certifications (DP-203, DP-600, or equivalent)

## Description

This is a client-facing engineering role on a long-term engagement. You will work directly with the clients technical leadership and U.S.-based stakeholders, so strong written and spoken English and the ability to drive your own work with minimal hand-holding are essential.

Core Technology Stack

Required - the work centers on the Microsoft data platform:

 * Microsoft Fabric - OneLake, Lakehouse, Warehouse, Pipelines, Notebooks, Dataflows Gen2
 * Azure SQL - schema design, performance tuning, indexing, partitioning, and security
 * Medallion Architecture on Fabric - hands-on experience designing and building Bronze / Silver / Gold layers in Microsoft Fabric and Azure SQL
 * T-SQL - advanced querying, stored procedures, window functions, performance optimization
 * ELT / ETL pipeline development - ingestion, transformation, orchestration, and monitoring across the Bronze Silver Gold flow
 * Data warehouse modeling - dimensional modeling (Kimball), slowly changing dimensions, conformed dimensions in the Gold layer

Strongly preferred - commonly paired with Fabric in client environments:

 * Azure Data Factory and/or Synapse Analytics
 * Power BI and DAX for semantic models and reporting
 * Python or PySpark for notebooks and transformations
 * Git-based source control and CI/CD for data pipelines (Azure DevOps or GitHub Actions)
 * Azure Data Lake Storage (Gen2) and Delta / Parquet formats

What You'll Do

 * Design and build data warehouse solutions on Microsoft Fabric and Azure SQL aligned to client business needs
 * Implement and evolve the Medallion Architecture - Bronze (raw), Silver (cleansed/conformed), and Gold (business-ready) layers - on Fabric and Azure SQL
 * Develop and maintain ELT/ETL pipelines that are reliable, observable, and easy to operate
 * Model data for analytics and reporting - fact/dimension design, conformed dimensions, performant aggregates
 * Collaborate with technical leads and client stakeholders to translate requirements into delivery-ready solutions
 * Own quality - testing, validation, documentation, and monitoring of pipelines and datasets
 * Research and propose solutions independently; bring options and tradeoffs, not just questions
 * Participate in code reviews and contribute to engineering standards on the account