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Azure Data Engineer Jobs in Wisconsin (NOW HIRING)

... Azure Data Engineer Associate, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the current and ...

... Azure Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies ...

Associate Data Engineer

Milwaukee, WI · On-site

$112.50K - $135.10K/yr

The Associate Data Engineer will design, build, and optimize modern data solutions, transforming ... T‑SQL, Python, Azure Data Factory/Fabric Data Pipelines, and Databricks; implement ...

Associate Data Engineer

Madison, WI · On-site

$115.50K - $138.60K/yr

The Associate Data Engineer will design, build, and optimize modern data solutions, transforming ... T‑SQL, Python, Azure Data Factory/Fabric Data Pipelines, and Databricks; implement ...

Sr. Fabric Data Engineer

Madison, WI

$106.80K - $145.10K/yr

Optimize data pipelines for performance, reliability, and cost efficiency across Azure and Fabric ... Partner with cloud engineering and security teams to optimize Fabric deployments integrated with ...

... Azure Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture ...

Preferred : • Experience with Azure Cloud infrastructure, including hybrid analytics workload configurations and networking. • Certifications in Azure Engineering (e.g., Azure Data Engineer ...

New

Tech Lead/Data Engineer III

Madison, WI · On-site

$100.30K - $172K/yr

Medica is seeking an experienced Tech Lead/Data Engineer III. This role is ideal for an innovative ... Azure Fundamentals * Snowflake SnowPro Core Certification * Snowflake Advanced Architect ...

Sr. Data Engineer

Madison, WI

$114.10K - $137.10K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI · On-site

$114.10K - $137.10K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI

$115.40K - $138.50K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

Sr. Data Engineer

Madison, WI

$114.10K - $137.10K/yr

The ideal candidate will possess expertise in Databricks and modern data engineering tools such as Azure Data Factory, combined with hands on experience working with biological, genomic, or other ...

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Azure Data Engineer information

See Wisconsin salary details

$44.9K

$130.9K

$179.2K

How much do azure data engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for azure data engineer in Wisconsin is $130,930.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,600.00 and $138,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Azure Data Engineer, and why are they important?

To thrive as an Azure Data Engineer, you need proficiency in data modeling, SQL, ETL processes, and a solid understanding of cloud computing concepts, typically supported by a degree in computer science or a related field. Familiarity with Microsoft Azure services (such as Azure Data Factory, Azure Synapse Analytics, and Azure Databricks), and relevant certifications like Microsoft Certified: Azure Data Engineer Associate, are highly valuable. Strong problem-solving skills, effective communication, and adaptability help you collaborate across teams and respond to evolving project needs. These skills are crucial for designing robust data solutions that support business intelligence and decision-making in cloud environments.

What are some common challenges Azure Data Engineers face when integrating data from multiple sources?

Azure Data Engineers often encounter challenges when consolidating data from diverse sources such as on-premises databases, cloud storage, and third-party applications. Issues like data format inconsistencies, varying data quality, and synchronization timing can complicate the integration process. Leveraging Azure services like Data Factory and Synapse Analytics helps automate and streamline these tasks, but careful planning and robust data validation are essential. Collaboration with business analysts and data architects is also crucial to ensure the integrated data meets organizational requirements.

What are Azure Data Engineers?

Azure Data Engineers are IT professionals who design, implement, and manage data solutions using Microsoft Azure cloud services. They are responsible for building data pipelines, integrating diverse data sources, and ensuring data is stored securely and efficiently. These engineers work with tools like Azure Data Factory, Azure Databricks, and Azure Synapse Analytics to process, transform, and analyze large volumes of data. Their main goal is to provide reliable data infrastructure to support business intelligence and analytics needs.

What is the difference between Azure Data Engineer vs Data Analyst?

AspectAzure Data EngineerData Analyst
Required CredentialsAzure certifications, SQL, Python, cloud skillsData analysis certifications, SQL, Excel, BI tools
Work EnvironmentCloud platforms, data pipelines, big data toolsData visualization, reporting, business insights
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail

Azure Data Engineers focus on building and maintaining data pipelines in cloud environments, utilizing tools like Azure Data Factory and SQL. Data Analysts interpret data to generate reports and insights, often using Excel and BI tools. While both roles work with data, Azure Data Engineers handle data infrastructure, whereas Data Analysts focus on data interpretation and visualization.

What are the most commonly searched types of Azure Data Engineer jobs in Wisconsin? The most popular types of Azure Data Engineer jobs in Wisconsin are:
What are popular job titles related to Azure Data Engineer jobs in Wisconsin? For Azure Data Engineer jobs in Wisconsin, the most frequently searched job titles are:
Infographic showing various Azure Data Engineer job openings in Wisconsin as of May 2026, with employment types broken down into 84% Full Time, 5% Part Time, and 11% Contract. Highlights an 79% Physical, 11% Hybrid, and 10% Remote job distribution, with an average salary of $130,930 per year, or $62.9 per hour.
Azure Data Engineer

$90K/yr

Other

Medical, Dental, Vision, Retirement

Posted 22 days ago


Job description

Schedule: Monday Friday from 8:30 5:30 ET

Our client is seeking for a Azure Data Engineer to join their team. As a Data Engineer, you ll help build the operational intelligence architecture that powers better-run businesses. You ll work side by side with clients and teammates to turn messy data into well designed, streamlined, and robust systems. Here s what that looks like:

  • Architect and implement Microsoft Fabric solutions that enable scalable, secure, and high-performance data platforms.
  • Design and build robust pipelines to bring together multiple data sources structured and unstructured into cohesive, reliable systems.
  • Ensure quality, maintainability, and resilience in all data engineering solutions, following best practices for testing, monitoring, and version control.
  • Collaborate with analysts, developers, and business stakeholders to translate requirements into technical designs that meet operational and strategic needs.
  • Participate in daily and weekly team check-ins, sharing progress, troubleshooting challenges, and contributing to architectural decisions.
  • Lead technical presentations and demos, building confidence in communicating complex engineering concepts to both technical and non-technical audiences.
  • Optimize data models and storage strategies for performance and scalability across reporting and AI-driven applications.
  • Write clean, efficient, and well-documented code in SQL, Python, Spark, and other relevant languages, ensuring solutions are fit for purpose and built to last.
  • Implement data governance and security standards, safeguarding sensitive information while enabling accessibility for authorized users.
  • Manage key components of engineering projects, growing into full ownership from design through deployment and ongoing maintenance.
  • Stay current with emerging technologies in data engineering, AI integration, and cloud architecture to continuously improve system capabilities.
  • Develop integrated agentic AI systems using Microsoft AI Foundry, ensuring seamless orchestration between AI components and enterprise data workflows.

What You Bring:

  • We re looking for someone who s curious, collaborative, and ready to grow fast. You ll thrive here if you:

Education:

  • Degree in Computer Science, Data Engineering, Information Systems, or related technical field (advanced degree or equivalent experience preferred).

Technical Expertise:

  • Real-world experience in Microsoft Fabric.
  • Experience with Microsoft AI Foundry for building integrated AI-driven solutions.
  • Strong skills in SQL and Python for data manipulation and automation.
  • Familiarity with Spark for distributed data processing.
  • Experience with Databricks (optional but highly preferred).
  • Understanding of data modeling, ETL processes, and pipeline orchestration.

Cloud & Platform Skills:

  • Hands-on experience with Azure Data Services (Data Lake, Synapse, etc.).
  • Familiarity with containerization and orchestration (Docker, Kubernetes) is a plus.

Development Practices:

  • Ability to write clean, maintainable, and well-documented code.
  • Strong grasp of version control (Git) and CI/CD pipelines.

Analytical & Problem-Solving:

  • Think critically and solve complex data engineering challenges with precision.
  • Embrace an Agile mindset and deliver in iterative stages.

Soft Skills:

  • Communicate clearly both in writing and verbally.
  • Detail-oriented, organized, and able to manage multiple priorities in a fast-paced environment.
  • Handle sensitive information with professionalism and discretion.

Certifications (Preferred):

  • Microsoft Certified: Azure Data Engineer Associate.
  • Microsoft Certified: Azure AI Engineer Associate.
  • Databricks Certified Data Engineer (optional but valuable).

Bonus Skills:

  • Experience with data governance, security, and compliance frameworks.
  • Familiarity with Power BI for validating data models and supporting analytics teams.

Salary: Annual salary of $90,000 + Benefits (Health Insurance, 401(k), Dental, Vision).

About The Company

Peterson Technology Partners (PTP) is an Equal Opportunity Employer committed to creating a transparent, inclusive, and human-centered hiring experience.

For more than 28 years, PTP has operated as one of the top IT staffing and recruiting firms in the USA built on trust, long-term partnerships, and technical excellence.

Based in the Chicago suburb of Park Ridge, IL, our team of more than 500 employees and consultants is dedicated to:

Helping every client make the best hiring decisions possible

Matching professionals with the right IT jobs and career opportunities

As part of that commitment, we believe in providing clear information about how our hiring technologies work and how your data is used. The following section outlines our AI-assisted interview process and your rights as a candidate.

AI-Assisted Interview Experience (Pete & Gabi Rebecca)

To provide a consistent, fair, and flexible experience for all candidates, we use AI-assisted tools to support parts of the interview process. This includes our proprietary AI platform Pete & Gabi, which includes AI recruiter Rebecca.

These AI hiring tools help us:

  • Conduct recorded video interviews
  • Transcribe interviews
  • Summarize candidate responses
  • Generate job-related insights
  • Streamline communication and scheduling

Please note that:

The AI does NOT make hiring decisions; all decisions are made by our human recruiters, hiring managers, or client partners.

The AI does not evaluate facial expressions, emotions, or physical traits; it is used only to support fairness, consistency, and efficiency.

If you prefer a non-AI interview format, we will gladly provide an alternative.

Technical or Case Interviews (Role-Dependent):

When applying for certain tech jobs, you may participate in:

  • A technical interview
  • A coding challenge
  • A case study
  • A client-specific assessment

We will always explain what to expect in advance so you can prepare with confidence.

Human Review & Selection:

Every candidate's profile including interviews, conversations, and assessments is reviewed by experienced recruiters and hiring leaders.

AI insights may assist with organization and evaluation, but final decisions are always human-driven.

Your Rights as a Candidate:

At PTP, every candidate has the right to:

Request a non-AI interview path

Ask how your data is being used

Request access to transcripts or interview recordings

Request deletion of your AI-recorded interview

Receive clear, timely communication

Our goal is to ensure you feel respected, informed, and supported throughout your experience.

Our Commitment:

For more than 28 years, PTP has focused on putting people first candidates, consultants, employees, and clients.

We're committed to a hiring process that is:

  • Transparent
  • Compliant
  • Equitable
  • Powered by innovative technology that enhances not replaces human judgment

Welcome to the future of hiring at Peterson Technology Partners.

We're excited to learn more about you.

Equal Employment Opportunity:

Peterson Technology Partners is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, national origin, gender identity, sexual orientation, disability, veteran status, or any other protected characteristic.