Senior Data Engineer – Azure & Microsoft Fabric

Title

Sr. Data Engineer(Azure/Fabric)

Location

Deerfield Beach, FL (Hybrid 3 days onsite, 2 days remote)

Duration

Long term contract with the potential to go perm in the future, but no guarantee,

Compensation

$75/hr -$80/hr

Work Requirements

U.S. Citizen, GC Holders, or Authorized to Work in the U.S.

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, 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
• Bachelor's degree in computer science/engineering or a related technical field, or equivalent

experience

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-cicd
• 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

About INSPYR Solutions

Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.