Senior Azure Fabric Data Engineer: Lakehouse & ML Pipelines

3Core Systems, Inc; Deerfield Beach (FL); On-site; USD 120,000 - 180,000; Full time

Job summary

3Core Systems, Inc in Deerfield Beach, FL is seeking an Azure Data Engineer with Fabric to design, build, test, and support data pipelines behind analytics, reporting, and ML on Azure and Fabric.

The role emphasizes ETL/ELT development, medallion lakehouse architectures, PySpark/T-SQL in Fabric Notebooks, and DevOps automation. Collaboration with data scientists and engineers is essential for success.

Qualifications

• Must be a team player with a get-it-done attitude.
• 15+ years of software development with relational databases.
• 5+ years of data engineering on Azure.
• Expert SQL/T-SQL, Python and PySpark skills.
• Hands-on experience with Microsoft Fabric: Lakehouse, Warehouse, Data Factory, Notebooks, OneLake.
• Experience with Azure DevOps CI/CD pipelines and Bicep.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines on Azure Data Factory and Fabric Data Factory.
• Develop medallion architecture (bronze, silver, gold) in Fabric Lakehouse and OneLake.
• Write transformations in PySpark, SparkSQL, and T-SQL in Fabric Notebooks.
• Replace legacy SAS/file-based ETL with governed pipelines including alerting and retries.
• Design ML pipelines with Data Science team: data prep, feature engineering, training, scoring.
• Manage model lifecycle with MLflow and model registry; move workloads to Fabric Data Science.
• Build and maintain Azure DevOps pipelines and Bicep templates for resources.
• Build dimensional models and Fabric semantic models for analytics.
• Implement data security, governance, and Purview lineage.

Job description

3Core Systems, Inc in Deerfield Beach, FL is seeking an Azure Data Engineer with Fabric to design, build, test, and support data pipelines behind analytics, reporting, and ML on Azure and Fabric.

The role emphasizes ETL/ELT development, medallion lakehouse architectures, PySpark/T-SQL in Fabric Notebooks, and DevOps automation. Collaboration with data scientists and engineers is essential for success.