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Azure Data Engineer Jobs in Canton, MI (NOW HIRING)

Stellantis

ICT Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Data engineering is the practice of making the appropriate data available to various data consumers ... Snowflake, Databricks AWS, Azure, GCP). * Strong communication and stakeholder engagement skills.

Pwc

Data Governance- Manager

Detroit, MI

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Ford Motor Company

Data Engineer

Dearborn, MI

$105K - $127K/yr

The Data Engineer role resides within the Ford's Electric Vehicle organization. In this role, you ... Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery.

Pwc

Data Engineer - Senior Associate

Detroit, MI · On-site

$77K - $202K/yr

... and Azure Data Factory to enhance data engineering capabilities - Applying data architecture development and database management skills to optimize data solutions - Leveraging Apache Airflow and ...

Infosys Limited

Azure Databricks Engineer

Ann Arbor, MI · On-site

$90 - $120/hr

Overview The Infosys Data and Analytics (DNA) unit is at the forefront of transforming data into ... Work with Azure Data Engineering stack (ADF, ADLS, Blob, Key Vault) and version control (Git/GitLab)

Infosys

Azure Databricks Engineer

Ann Arbor, MI · On-site

... Azure Data Engineering stack (ADF, ADLS, Blob, Key Vault) and version control (Git/GitLab ... Overview The Infosys Data and Analytics (DNA) unit is at the forefront of transforming data into ...

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related ... We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful ...

Hearst Newspapers

Full-Stack Data Engineer

Troy, MI

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst Television

Full-Stack Data Engineer

Troy, MI

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

Experience with Git and Azure DevOps * Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks) * Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray) Helpful Experience ...

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Showing results 41-60

All JobsAzure Data Engineer JobsAzure Data Engineer Jobs in Canton, MI

Azure Data Engineer information

See Canton, MI salary details

$41.2K

$120.2K

$164.5K

How much do azure data engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for azure data engineer in Canton, MI is $120,215.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $127,400.00 per year, depending on experience, location, and employer.

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 key skills and qualifications needed to thrive as an Azure Data Engineer?

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 is an Azure Data Engineer?

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.

Is an Azure Data Engineer a good career?

An Azure Data Engineer is a valuable role focused on designing and implementing data solutions using Microsoft Azure cloud services. It typically requires skills in data modeling, SQL, and tools like Azure Data Factory and Databricks, with certifications such as Microsoft Certified: Azure Data Engineer Associate enhancing job prospects. The role offers strong demand due to the increasing reliance on cloud-based data management and analytics.
What are popular job titles related to Azure Data Engineer jobs in Canton, MI? For Azure Data Engineer jobs in Canton, MI, the most frequently searched job titles are:
What job categories do people searching Azure Data Engineer jobs in Canton, MI look for? The top searched job categories for Azure Data Engineer jobs in Canton, MI are:
What cities near Canton, MI are hiring for Azure Data Engineer jobs? Cities near Canton, MI with the most Azure Data Engineer job openings:
Azure Data Engineer jobs near you
Infographic showing various Azure Data Engineer job openings in Canton, MI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $120,215 per year, or $57.8 per hour.

ICT Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 11 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

We are seeking a strategic and hands-on Data Engineer to support Purchasing and Finance Analytics and Programs within our North America Data & AI team. Data engineering is the practice of making the appropriate data available to various data consumers (including data scientists, data and business analysts, citizen integrators, and line-of-business users). It is a discipline that involves collaboration across business and IT units.
In addition to creating and maintaining an optimal pipeline architecture, typical duties and responsibilities for a Data Engineer position may include:
The ideal candidate combines strong analytical skills with practical experience building scalable analytics, models, and data products in enterprise environments. You will be part of a talented team of data scientists, engineers, driving predictive analytics and early detection of emerging warranty trends using vast datasets across the enterprise.
Key Responsibilities:
  • Assembling large, complex sets of data that meet non-functional and functional business requirements
  • Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
  • Develop robust ETL (Extract, Transform, Load) process to integrate data from various sources.
  • Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
  • Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS, Azure, DB2 and SQL technologies
  • Building scalable tables to provide actionable insight into key business performance metrics including operational efficiency and customer acquisition
  • Working with stakeholders including the Data Product teams to support their data infrastructure needs while assisting with data-related technical issues
  • Design and maintain data models, schemas, and database structures to support analytical and operational use cases.
  • Optimize data storage and retrieval mechanisms for performance and scalability.
  • Lead and coordinate cross-functional AI programs from concept to deployment, ensuring alignment with business goals and timelines.
  • Collaborate with other data scientists, engineers, and business stakeholders to define and prioritize program objectives.
  • Apply statistical analysis and machine learning techniques to solve business and operational problems.
  • Partner with business stakeholders to understand requirements and translate them into analytical solutions.
  • Translate business needs into actionable AI use cases and technical requirements
  • Build and deploy predictive models to forecast warranty claims, failure rates, and cost trends.
  • Ensure data quality, lineage, documentation, and compliance with governance requirements
  • Create dashboards and analytical outputs that drive insight adoption and operational impact
  • Collaborate with business data engineers, and platform teams on scalability, performance, and best practices

Basic Qualifications
  • Bachelor's or in Data Science, Statistics, Engineering, Computer Science, or related field.
  • Minimum 3 years' experience as Data Scientist, Advanced Analyst, or similar role
  • Strong proficiency in Python, SQL, PySpark and visualization tools (e.g., Power BI, Foundry Workshop).
  • Solid understanding of statistics, exploratory data analysis, and applied machine learning.
  • Experience working with large, complex datasets in enterprise environments
  • Ability to communicate analytical findings clearly to technical and non-technical audiences.
  • Proven experience delivering end-to-end analytics or data science solutions into production.
  • Experience with one or two data and cloud platforms (e.g., Palantir Foundry. Snowflake, Databricks AWS, Azure, GCP).
  • Strong communication and stakeholder engagement skills.

Preferred Qualifications
  • Familiarity with data modeling, semantic layers, and enterprise data platforms.
  • Industry experience in automotive and manufacturing
  • Exposure to MLOps concepts, model deployment, or monitoring
  • Hands-on experience with Palantir Foundry, Snowflake Intelligence
  • Master's degree in Data Science, Statistics, Engineering, Computer Science, or related field.
  • This is a fast-paced environment providing rapid delivery for our business partners. You will be working in a highly collaborative environment that values speed and quality, with a strong desire to drive change and value.

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