Azure Data Engineer with Fabric

Role

Azure Data Engineer with Fabric

Location

Deerfield Beach, FL

Duration

6-12 Month Contract to Hire

NEED AN SME WITH FABRIC.

Senior Data Engineer – Azure & Microsoft 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 such as Azure Synapse, Azure SQL, SQL Server, and ADLS Gen2. That data lands in Fabric Lakehouse and Warehouse on OneLake through Azure Data Factory and Fabric Data Factory 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 through Azure DevOps pipelines, and set up supporting Azure resources with Bicep templates.
• They will apply secure data practices (Managed Identity, Microsoft Entra ID, Key Vault, OneLake security, and Microsoft Purview) 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 Data Factory, 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 (Azure DevOps 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 Azure Synapse, 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, Spark SQL, 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 include alerting, retries, and the ability to re-run.
• Design and develop

ML pipelines with the Data Science team

data preparation, feature engineering, model training, and batch scoring (Fabric PREDICT). Publish model outputs to Lakehouse tables for Power BI (Direct Lake) reporting.

• Manage the model lifecycle with MLflow experiment tracking and the model registry, and help move Azure Machine Learning workloads to Fabric Data Science.
• Build and maintain Azure DevOps CI/CD pipelines (YAML) for ADF, Fabric items, notebooks, SQL objects, and ML assets. This includes Git integration, branching strategy, pull-request validation, and promotion between Dev and Prod workspaces.
• Write and maintain Bicep templates that set up supporting 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 and Fabric semantic models for analytics and reporting.

Apply data security and compliance controls

Managed Identity and Entra ID authentication, Key Vault secrets, OneLake and workspace roles, row- and column-level security, data masking, and sensitivity labels.

• Build data quality checks, lineage, and cataloging (Microsoft Purview) into every data-movement process.
• Monitor, troubleshoot, and tune pipelines, Spark jobs, and queries for performance and capacity cost using the Fabric Monitoring Hub and Azure Monitor.
• Work with stakeholders to turn business requirements into technical specifications, and keep design specifications and component documents up to date.
• Keep up with the Azure and Microsoft Fabric roadmap and recommend generally available features and best practices to adopt.

Qualifications And Requirements

• Must be a team player with a get-it-done attitude
• 15+ years of software development with relational databases, including 5+ years of data engineering on Azure
• Must have developed and deployed at least 15 Azure Data Factory or Fabric Data Factory pipelines to production following SDLC processes
• Expert SQL/T-SQL skills and strong Python and PySpark 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 data services

Azure Data Factory, Azure Synapse, Azure SQL, and ADLS Gen2

• Experience building ML pipelines and supporting data scientists (feature engineering, training and scoring pipelines, MLflow, Azure Machine Learning, or Fabric Data Science)
• Experience with Azure DevOps (Repos, YAML Pipelines, Boards) and CI/CD for data solutions
• Experience writing infrastructure as code with Bicep (ARM experience; Terraform is a plus)
• Strong knowledge of data modeling, medallion architecture, Delta Lake, and relational and non-relational databases

Knowledge of data security and governance

Entra ID, 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 an Agile environment
• Eager to share knowledge with teammates in all forums and eager to learn from them. Strong initiative to find ways to improve solutions, systems, and processes

Must have skills

• Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Notebooks, OneLake)
• Azure Data Factory and ETL/ELT design
• SQL/T-SQL, Python, PySpark
• ML pipeline concepts (feature engineering, training, batch scoring, MLflow)
• Azure DevOps CI/CD pipelines
• Bicep / Infrastructure as Code
• Data Lake / Lakehouse and medallion architecture

Nice-to-have skills

• Azure Synapse Analytics and Azure Databricks
• Microsoft Purview
• Power BI semantic models and Direct Lake
• Fabric Real-Time Intelligence (Eventstream, KQL)
• GitHub Enterprise and Fabric CI/CD
• Experience migrating SAS workloads

1 or more certifications

Microsoft Certified

Fabric Data Engineer Associate (DP-700)

Microsoft Certified

Fabric Analytics Engineer Associate (DP-600)

• Azure Data Scientist Associate (DP-100)
• Azure DevOps Engineer Expert (AZ-400)
• Azure Data Engineer Associate (DP-203, retired but still recognized)