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Entry Level Microsoft Data Engineer Jobs in Detroit, MI

Data / BI Architect

Pontiac, MI · On-site

$63.25 - $81.50/hr

... Microsoft Power BI, Tableau, R Programming for data visualizations, Python, TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Databricks, Jupyter Notebooks, AWS (SageMaker, EC2, S3), Azure ...

Experience a level of variety and responsibility rarely available in entry-level roles If you enjoy ... Familiarity with Windows Operating Systems, Microsoft Tools, and basic networking You'll Stand Out ...

Cloud Automation Engineer

Allen Park, MI

$50.75 - $68/hr

The CT solution combines comprehensive data acquisition methods with a powerful edge and cloud ... Developing Microsoft Azure Solutions) * Experience delivering infrastructure for distributed ...

Cloud Automation Engineer

Allen Park, MI · On-site

$50.75 - $68/hr

The CT ® solution combines comprehensive data acquisition methods with a powerful edge and cloud ... Developing Microsoft Azure Solutions) * Experience delivering infrastructure for distributed ...

Microsoft Power BI Certification (PL-300) or equivalent Business Intelligence certification ... digital, engineering, cloud and AI, powered by a broad portfolio of technology services and ...

New

Showing results 21-40

Entry Level Microsoft Data Engineer information

See Detroit, MI salary details

$44.1K

$128.4K

$175.7K

How much do entry level microsoft data engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for entry level microsoft data engineer in Detroit, MI is $128,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,400.00 and $136,100.00 per year, depending on experience, location, and employer.

What does an entry level Microsoft data engineer do?

An Entry Level Microsoft Data Engineer is responsible for designing, building, and maintaining data solutions using Microsoft technologies such as Azure Data Factory, SQL Server, and Power BI. Their role typically involves collecting, transforming, and loading (ETL) data from various sources to enable data analysis and reporting. They work closely with other IT professionals to ensure data integrity, performance, and security while learning best practices in data engineering. This position is ideal for those starting their careers in data engineering and looking to develop expertise in Microsoft's data ecosystem.

What are the key skills and qualifications needed to thrive as an entry level Microsoft data engineer?

To thrive as an Entry Level Microsoft Data Engineer, you need foundational knowledge of SQL, data modeling, and a relevant degree in computer science or a related field. Familiarity with Microsoft technologies such as Azure Data Factory, SQL Server, Power BI, and possibly certifications like Microsoft Certified: Azure Data Engineer Associate are typically expected. Strong analytical thinking, attention to detail, and effective communication help you stand out when collaborating with teams and translating data requirements. These skills are crucial for ensuring reliable data pipelines, facilitating data-driven decisions, and supporting organizational growth.

What are some common challenges faced by entry level Microsoft data engineers when working with large datasets?

Entry-level Microsoft Data Engineers often encounter challenges such as ensuring data integrity during extraction, transformation, and loading (ETL) processes, especially when dealing with large or complex datasets in Azure environments. Optimizing query performance and managing resource costs can also be difficult for those new to cloud-based data solutions. However, these challenges are excellent learning opportunities, as they encourage developing strong troubleshooting skills and familiarity with tools like Azure Data Factory, SQL Server, and Power BI. Support from more experienced team members and access to structured onboarding programs can help new hires quickly become proficient and confident in their daily responsibilities.

What is the difference between Entry Level Microsoft Data Engineer vs Data Analyst?

AspectEntry Level Microsoft Data EngineerData Analyst
Required CredentialsMicrosoft certifications, SQL, basic cloud knowledgeExcel, SQL, data visualization tools
Work EnvironmentData pipelines, cloud platforms, database managementData interpretation, reporting, dashboards
Industry UsageTech, finance, healthcare with data infrastructure needsMarketing, retail, finance for insights and reporting

Both roles often require SQL and basic data skills, but Data Engineers focus on building data systems and pipelines, while Data Analysts interpret data and create reports. Entry Level Microsoft Data Engineers typically work more with cloud platforms and data infrastructure, whereas Data Analysts focus on data visualization and insights. The roles are complementary but differ in technical depth and focus areas.

What cities near Detroit, MI are hiring for Entry Level Microsoft Data Engineer jobs?

Cities near Detroit, MI with the most Entry Level Microsoft Data Engineer job openings:

Infographic showing various Entry Level Microsoft Data Engineer job openings in Detroit, MI as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $128,415 per year, or $61.7 per hour.

$16.75 - $21.50/hr

Full-time, Internship

Posted 25 days ago


Job description

Navitas Systems LLC, a leader in comprehensive energy storage solutions, was formed in 2011 with the merger of MicroSun Innovative Energy Storage Solutions and MicroSun Electronics, and the acquisition of lithium battery company A123 Systems’ Government Solutions Group. In 2019, East Penn Manufacturing, one of the world’s leading battery manufacturers, acquired majority interest in Navitas Systems. In SEVEN remarkable decades, East Penn has grown from a one-room shop with a product line of five automotive batteries to one of the world’s leading battery manufacturers with over 10,500 full-time employees, 515 product designs, operations around the world, and hundreds of awards for industry excellence.

At our Navitas facilities we engage in the research, design, development, and manufacture of advanced lithium cells and energy storage products and systems for both commercial customers and U.S. Government/military customers. We invest in our people, they are and always will be the heart of this company. Are you ready to join a family-owned enterprise committed to honoring the contributions of everyone? Then Navitas is the right place for you.


Navitas Systems is currently seeking a curious and technically strong Data Engineering Intern to join our BIS (Business Intelligence & Systems) team. The intern will help build and maintain the data pipelines, integrations, and warehouse infrastructure that power analytics, reporting, and decision-making across Navitas.

This is a hands-on opportunity to work directly with enterprise systems and contribute to the foundation of a modern data platform being built from the ground up. The intern will gain real-world experience in SQL development, ETL/ELT design, data modeling, and integration patterns in a fast-paced manufacturing environment.

Working hours will be scheduled around the intern's class schedule, but must be the same days and hours each week. The intern is expected to confirm their weekly schedule with their manager within two weeks of their start date.***Candidate must be lawful permanent resident or US Citizen and be able to work on site in Ann Arbor, MI


  • Assist in designing, building, and maintaining ETL/ELT pipelines that move data from source systems (ERP, MES, CRM, SharePoint, Excel) into the central data warehouse.
  • Write, optimize, and troubleshoot SQL queries, stored procedures, and views against SQL Server databases.
  • Support the design and implementation of star schema models, data marts, and semantic layers that feed Power BI and downstream consumers.
  • Help connect and integrate enterprise systems (Expandable ERP, Ignition MES, Salesforce, Dayforce, Jira) into the central data platform.
  • Build and run validation checks to ensure accuracy, completeness, and consistency of data flowing through pipelines.
  • Contribute to scheduled jobs, refresh cadences, and automation efforts that reduce manual data movement and reporting overhead.
  • Assist in monitoring pipeline health, identifying failures, and resolving data issues in partnership with IT and BIS team members.
  • Document data sources, transformations, schemas, and lineage; contribute to data governance and metric standardization efforts.
  • Use Jira to manage work items and SharePoint to publish documentation; collaborate with BI developers, analysts, and business stakeholders.

Required
  • Currently pursuing a Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field.
  • Must be a US Citizen or have a valid green card
  • Must be able to work on site at our Ann Arbor location
  • Strong working knowledge of SQL (joins, aggregations, subqueries, window functions) against relational databases.
  • Familiarity with SQL Server or comparable RDBMS (PostgreSQL, MySQL, Oracle).
  • Understanding of ETL/ELT concepts, data warehousing fundamentals, and relational data modeling.
  • Proficiency in at least one scripting language (Python preferred; PowerShell or similar acceptable).
  • Familiarity with Microsoft SharePoint for collaboration and documentation.
  • Familiarity with Jira (or similar work management tools) for tracking tasks and stories.
Preferred
  • Exposure to Power BI (semantic models, Power Query, DAX basics).
  • Familiarity with star schema / dimensional modeling (Kimball methodology).
  • Experience with Git and version control workflows.
  • Exposure to cloud data platforms (Azure, Fabric, OneLake, Databricks, Snowflake) or on-premises data lake/lakehouse concepts.
  • Familiarity with APIs, REST, JSON, and integration patterns between SaaS systems.
  • Exposure to MES, ERP, or manufacturing data environments.
  • Understanding of data governance, lineage, and metadata management concepts.
  • Coursework or projects involving data pipelines, distributed systems, or large-scale data processing.