10249

3Core Systems, Inc

Deerfield Beach (FL)

On-site

USD 140,000 - 190,000

Full time

2 days ago

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Job summary

3Core Systems, Inc. is seeking an Azure Data Engineer with Fabric to design and run scalable data pipelines across lakehouse architectures on Azure.

You will ingest, transform, and model data from sources like Azure Synapse, Azure SQL, and ADLS Gen2, building pipelines in Data Factory and Fabric Data Factory. Collaboration with data scientists and engineers is essential.

Qualifications

Fifteen plus years of software development with relational databases and five plus years in data engineering on Azure.
Proven track record deploying at least 15 Azure Data Factory or Fabric Data Factory pipelines to production.
Strong SQL/T-SQL, Python and PySpark debugging skills in MS SQL.
Hands-on experience with Fabric Lakehouse, Warehouse, Data Factory pipelines and Notebooks.
Experience designing medallion (bronze/silver/gold) architectures and data modeling.

Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory and Fabric Data Factory.
Develop ML pipelines with the Data Science team and publish outputs to Lakehouse tables for reporting.
Automate builds and releases via Azure DevOps pipelines and manage CI/CD for data solutions.
Implement data security, governance, and data quality checks across pipelines.
Collaborate with stakeholders to translate requirements into technical specifications.

Skills

Azure Data Factory

Microsoft Fabric

SQL/T-SQL

Python

PySpark

ETL/ELT

Data Modeling

Delta Lake / Lakehouse

Notebooks

Azure DevOps

Azure Data Factory pipelines

Tools

Fabric Data Factory

Bicep

Terraform (CI/CD)

GitHub

OneLake

Job description

Deerfield Beach, United States | Posted on 10/19/2026

Role: Azure Data Engineer with Fabric
Location: Deerfield Beach, FL
Duration: 6-12 Month Contract to Hire

NEED AN SME WITH FABRIC.

The Senior Data Engineer designs, builds, tests,and supports the data pipelines and data products behind our analytics,reporting, and machine learning work on Azure and Microsoft Fabric.
The role focuses on data engineering: ingesting,transforming, and modeling structured and unstructured data from sources suchas Azure Synapse, Azure SQL, SQL Server, and ADLS Gen2. That data lands in FabricLakehouse and Warehouse on OneLake through Azure Data Factory and Fabric DataFactory pipelines, Dataflow Gen2, and PySpark notebooks.
The engineer will also design and run machine learning(ML) pipelines with the Data Science team, automate builds and releases throughAzure DevOps pipelines, and set up supporting Azure resources with Biceptemplates.
They will apply secure data practices (ManagedIdentity, Microsoft Entra ID, Key Vault, OneLake security, and MicrosoftPurview) and build data quality, lineage, and governance into every pipeline.
This role works closely with Data Scientists,Solution Architects, Software Engineers, DevOps Engineers, QA Engineers,Project Managers, Information Security Engineers, and Delivery Managers.

What You Will Be Doing

Tech Breakdown (Coding and Collaboration)
10% Data Exploration and Design (Source Analysis, Data Modeling, Security, Quality, Performance)
40% ETL/ELT Pipeline Development (Azure DataFactory, Fabric Data Factory, Dataflow Gen2, Fabric Notebooks, Unit Testing)
20% ML Pipeline Design and Development (Data Preparation, Feature Engineering, Training and Batch Scoring Pipelines, MLflow)
20% DevOps and Infrastructure as Code (AzureDevOps CI/CD Pipelines, Bicep Templates, Fabric Workspace Promotion, Release Management)
10% Data Operations and Governance (Monitoring, Purview Lineage, Access Control, Cost and Performance Optimization)

Key Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory and Microsoft Fabric Data Factory(pipelines, Copy activity, Dataflow Gen2). These pipelines pull data from AzureSynapse, Azure SQL, SQL Server, APIs, and file-based sources.
Build a medallion architecture (bronze, silver,gold) in Fabric Lakehouse and Warehouse on OneLake using Delta Parquet tables,with shortcuts and mirroring where they fit.
Write data transformations in PySpark, SparkSQL, and T-SQL in Fabric Notebooks, and build reusable, parameterized,metadata-driven pipeline frameworks.
Replace legacy SAS and file-based ETL processes(CSV exports, file shares) with governed ADF and Fabric pipelines that includealerting, retries, and the ability to re-run.
Design and develop ML pipelines with the DataScience team: data preparation, feature engineering, model training, and batchscoring (Fabric PREDICT). Publish model outputs to Lakehouse tables for PowerBI (Direct Lake) reporting.
Manage the model lifecycle with MLflowexperiment tracking and the model registry, and help move Azure MachineLearning workloads to Fabric Data Science.
Build and maintain Azure DevOps CI/CD pipelines(YAML) for ADF, Fabric items, notebooks, SQL objects, and ML assets. Thisincludes Git integration, branching strategy, pull-request validation, andpromotion between Dev and Prod workspaces.
Write and maintain Bicep templates that set upsupporting Azure resources the same way in every environment (Data Factory,ADLS Gen2, Key Vault, managed identities, private endpoints, and networking).
Build dimensional (star schema) data models andFabric semantic models for analytics and reporting.
Apply data security and compliance controls:Managed Identity and Entra ID authentication, Key Vault secrets, OneLake andworkspace roles, row- and column-level security, data masking, and sensitivitylabels.
Build data quality checks, lineage, andcataloging (Microsoft Purview) into every data-movement process.
Monitor, troubleshoot, and tune pipelines, Sparkjobs, and queries for performance and capacity cost using the Fabric MonitoringHub and Azure Monitor.
Work with stakeholders to turn businessrequirements into technical specifications, and keep design specifications andcomponent documents up to date.
Keep up with the Azure and Microsoft Fabricroadmap and recommend generally available features and best practices to adopt.

Qualifications And Requirements

Must be a team player with a get-it-doneattitude
15+ years of software development withrelational databases, including 5+ years of data engineering on Azure
Must have developed and deployed at least 15Azure Data Factory or Fabric Data Factory pipelines to production followingSDLC processes
Expert SQL/T-SQL skills and strong Python andPySpark skills; demonstrable debugging skills in MS SQL
Hands-on experience with Microsoft Fabric:Lakehouse, Warehouse, Data Factory pipelines, Dataflow Gen2, Notebooks,OneLake, and semantic models
Demonstrable experience with Azure dataservices: Azure Data Factory, Azure Synapse, Azure SQL, and ADLS Gen2
Experience building ML pipelines and supportingdata scientists (feature engineering, training and scoring pipelines, MLflow,Azure Machine Learning, or Fabric Data Science)
Experience with Azure DevOps (Repos, YAMLPipelines, Boards) and CI/CD for data solutions
Experience writing infrastructure as code withBicep (ARM experience; Terraform is a plus)
Strong knowledge of data modeling, medallionarchitecture, Delta Lake, and relational and non-relational databases
Knowledge of data security and governance: EntraID, Managed Identity, Key Vault, Microsoft Purview, and private networking
Follow best practices and coding standards(e.g., code reviews, logging and instrumentation, static/dynamic code analysis,code coverage, unit and integration tests)
Work with Product Managers, Solution Architects,DevOps, and Information Security teams to understand data requirements in anAgile environment
Eager to share knowledge with teammates in allforums and eager to learn from them. Strong initiative to find ways to improvesolutions, systems, and processes