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Data Optimization Jobs in Michigan (NOW HIRING)

Stellantis

ICT Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

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 ...

Stantec

Senior Data Architect

Detroit, MI · On-site

$66.50 - $89/hr

Oversee the performance optimization, scalability and reliability of the PM2PA data flows. This may involve tuning Oracle databases or other key data sources, optimizing application performance and ...

Stellantis

ICT Data Engineer

Auburn Hills, MI

$108K - $130K/yr

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 ...

FastTek

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Data Engineer #1060557 Position Description: Employees in this job function are responsible for ... Ensure optimum performance and identify improvement opportunities Skills Required: * GitHub, Google ...

MM International

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Identify, analyze, and resolve complex technical issues related to WorkForce Software, integrations, and data processes, ensuring system stability and optimal performance. · Documentation: Create ...

FastTek

Data Engineer

Dearborn, MI

$105K - $126K/yr

Ensure optimum performance and identify improvement opportunities * Experience in Data ingestion for all types of data and data wrangling and transformations and land data in Big Query. * Experience ...

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

You will develop analytics products using your expertise in visualization, AI/ML, Statistics and Optimization using GDI&A approved packages and architectures. You will collaborate with Data Engineers ...

Orbotech

Aftermarket Business Data Analyst

Ann Arbor, MI

$77K - $132K/yr

Support inventory optimization, fill-rate performance, supply-demand balancing, and forecasting ... Strong proficiency in data analysis, visualization, and reporting tools. * Advanced analytical and ...

Corning

$104K - $125K/yr

... optimization, and delivery of complex ETL/ELT pipelines and distributed data-processing solutions. - Establish and promote Data Engineering standards, development patterns, data-quality frameworks ...

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Data Optimization information

What are some typical challenges faced in a data optimization role?

Professionals in Data Optimization often encounter challenges such as working with incomplete or inconsistent datasets, integrating data from multiple sources, and ensuring data quality and accuracy throughout the optimization process. Balancing technical efficiency with business objectives and communicating complex analytical findings in easily understandable ways can also be demanding. Collaboration with cross-functional teams is frequent, requiring both strong technical and interpersonal skills. Overcoming these challenges helps ensure that optimization projects deliver meaningful value and measurable impact for the organization.

What is a data optimization?

A Data Optimization job involves improving the efficiency, accuracy, and accessibility of data within an organization. Professionals in this role analyze large datasets, refine data structures, and implement strategies to enhance data processing and storage. They work with data engineers, analysts, and business teams to ensure data supports performance goals and decision-making. Common tasks include cleaning data, reducing redundancies, and optimizing database queries.

What are the key skills and qualifications needed to thrive in data optimization, and why are they important?

To thrive in Data Optimization, you need strong analytical skills, expertise in data modeling, and a solid foundation in statistics or mathematics, usually supported by a relevant degree. Familiarity with tools such as SQL, Python, R, and data visualization platforms like Tableau, as well as certifications in data analytics or optimization software, is highly beneficial. Effective communication, problem-solving abilities, and a collaborative mindset are key soft skills for this role. These competencies are crucial for translating complex data into actionable insights that drive business efficiency and performance improvements.

What are the most commonly searched types of Data Optimization jobs in Michigan? The most popular types of Data Optimization jobs in Michigan are:
What are popular job titles related to Data Optimization jobs in Michigan? For Data Optimization jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Optimization jobs in Michigan look for? The top searched job categories for Data Optimization jobs in Michigan are:
Data Optimization jobs near you
Infographic showing various Data Optimization job openings in Michigan as of August 2026, with employment types broken down into 86% Full Time, 7% Part Time, and 7% Temporary. Highlights an 100% In-person job distribution.

ICT Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 6 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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