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Data Analytics Engineer Jobs in Warren, MI (NOW HIRING)

Stellantis

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process ...

Belcan

Automotive Data Analyst

Dearborn, MI · Hybrid

$30 - $35/hr

This pivotal role is ideal for candidates with a robust background in data analytics for engineering who are seeking to continue their career in the automotive industry. Responsibilities: * Safety ...

Tech Tammina LLC

Data Analyst

Warren, MI · On-site

... Engineering, or a related quantitative field * Minimum 5 years of experience in data analytics ... business intelligence, or data-driven consulting * Experience supporting Sales and Marketing ...

FastTek

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design and develop analytical tools, algorithms, and programs to support data engineering activities like writing scripts and automating tasks * Ensure optimum performance and identify improvement ...

Contact Government Services, LLC

Data Engineer

Detroit, MI · On-site

$112K - $152K/yr

Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business Intelligence platform focused on providing solutions that empower ...

Contact Government Services, LLC

Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business Intelligence platform focused on providing solutions that empower ...

HTC Global Services

Data Engineer

Farmington Hills, MI · On-site

$112K - $135K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Data Engineer (Azure, Microsoft Dynamics 365 & Power BI) Overview / Summary The Data Engineer is ... Develop and maintain data structures within the data lake to support reporting and analytics.

HTC Global Services

Data Engineer

Farmington Hills, MI · On-site

$112K - $135K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Data Engineer (Azure, Microsoft Dynamics 365 & Power BI) Overview / Summary The Data Engineer is ... Develop and maintain data structures within the data lake to support reporting and analytics.

FastTek

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Data/Analytics * ETL * Application Development * Google Cloud Platform Experience Required: * Engineer 3 Exp: 7+ years Data Engineering work experience Experience Preferred: Our preferred ...

Stefanini Group

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Design and develop analytical tools, algorithms, and programs to support data engineering activities, including writing scripts and automating tasks. * Ensure optimum performance and identify ...

Stefanini

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Design and develop analytical tools, algorithms, and programs to support data engineering activities, including writing scripts and automating tasks. Ensure optimum performance and identify ...

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Showing results 41-60

All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Warren, MI

Data Analytics Engineer information

See Warren, MI salary details

$41.8K

$121.8K

$166.7K

How much do data analytics engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data analytics engineer in Warren, MI is $121,834.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $129,100.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

What are the key skills and qualifications needed to thrive as a data analytics engineer, and why are they important?

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What are the most commonly searched types of Data Analytics Engineer jobs in Warren, MI? The most popular types of Data Analytics Engineer jobs in Warren, MI are:
What are popular job titles related to Data Analytics Engineer jobs in Warren, MI? For Data Analytics Engineer jobs in Warren, MI, the most frequently searched job titles are:
What job categories do people searching Data Analytics Engineer jobs in Warren, MI look for? The top searched job categories for Data Analytics Engineer jobs in Warren, MI are:
What cities near Warren, MI are hiring for Data Analytics Engineer jobs? Cities near Warren, MI with the most Data Analytics Engineer job openings:
Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Warren, MI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $121,834 per year, or $58.6 per hour.

Data Engineer

Stellantis

Auburn Hills, MI

$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

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process massive datasets in both batch and real-time. You will work at the intersection of software engineering and data science, ensuring that our data architecture is scalable, reliable, and follows industry best practices. 

Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to, the following responsibilities: 

  • Pipeline Development: Design and implement complex data processing pipelines using Apache Spark. 
  • Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing. 
  • Infrastructure as Code: Manage and provision cloud infrastructure using Terraform. 
  • CI/CD & Automation: Streamline development workflows by implementing and maintaining GitHub Actions for automated testing and deployment. 
  • Code Quality: Uphold rigorous software engineering standards, including comprehensive unit/integration testing, code reviews, and maintainable documentation. 
  • Collaboration: Work closely with stakeholders to translate business requirements into technical specifications. 

Basic Qualifications: 

  • Bachelors degree in Computer Science, Engineering, Mathematics, or a related technical discipline  
  • A minimum of 5 years of experience in the data engineering and software development life cycle. Including:
    • A minimum of 4 years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores. 
    • A minimum of 4 years of hands-on experience working with AWS cloud services  
  • Comprehensive experience with one or more programming languages such as Python, Java, or Rust 
  • Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.) 
  • Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more 
  • Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.) 
  • Experience with designing and implementing real-time pipelines 
  • Experience with data quality and validation 
  • Experience with API design 
  • Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming). 
  • Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment. 
  • SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.

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