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Internship Financial Data Engineer Jobs in Michigan

ICT Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

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 ...

Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... financial resources. We combine cutting-edge technology with world-class personnel to deliver ...

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to ... markets, including financial services, manufacturing, telecommunications, chemical services ...

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to ... markets, including financial services, manufacturing, telecommunications, chemical services ...

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to ... markets, including financial services, manufacturing, telecommunications, chemical services ...

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to ... markets, including financial services, manufacturing, telecommunications, chemical services ...

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to ... markets, including financial services, manufacturing, telecommunications, chemical services ...

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a GCP Data Engineer, Dearborn, MI For quick apply, please reach out to ... markets, including financial services, manufacturing, telecommunications, chemical services ...

Senior Data Engineer

Lansing, MI · On-site

$107K - $146K/yr

Senior Data Engineer Job Location: Lansing, MI (Hybrid) Job Type: Contract / Requirement: * 3-7 ... Experience analyzing project, portfolio, financial, and operational data. * Excellent analytical ...

Data Engineer - Resource Demand

Warren, MI · On-site +1

$107K - $129K/yr

Python or similar programming languages, advanced SQL, relational and analytical data platforms ... Experience connecting planning, workforce, finance, portfolio, and actuals data to support ...

Senior Data Engineer

Lansing, MI · On-site

$107K - $146K/yr

Senior Data Engineer #1061723 Position Summary: The Michigan Department of Technology, Management ... Analyze project, portfolio, financial, schedule, resource, governance, and operational data to ...

Data Engineer - Resource Demand

Warren, MI · On-site

$107K - $129K/yr

Python or similar programming languages, advanced SQL, relational and analytical data platforms ... Experience connecting planning, workforce, finance, portfolio, and actuals data to support ...

Data Engineer

Dearborn, MI · On-site

$140K - $184K/yr

By partnering with dealerships, we provide financing, personalized service and professional ... Design and build production data engineering solutions to deliver reusable patterns using Google ...

Google Cloud Platform Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a Google Cloud Platform Data Engineer, Dearborn, MI For quick apply ... markets, including financial services, manufacturing, telecommunications, chemical services ...

Google Cloud Platform Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a Google Cloud Platform Data Engineer, Dearborn, MI For quick apply ... markets, including financial services, manufacturing, telecommunications, chemical services ...

Showing results 21-40

Internship Financial Data Engineer information

What are the key skills and qualifications needed to thrive as an internship financial data engineer?

To thrive as an Internship Financial Data Engineer, you need a solid grasp of statistics, programming (especially Python or R), and foundational knowledge of finance or economics, typically supported by relevant coursework or a related degree. Familiarity with data visualization tools (like Tableau), SQL databases, and cloud platforms such as AWS or Azure is often expected. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex data and collaborate with teams. These abilities are crucial for transforming raw financial data into actionable insights and supporting data-driven decision-making in financial organizations.

What is the difference between Internship Financial Data Engineer vs Financial Data Analyst?

AspectInternship Financial Data EngineerFinancial Data Analyst
Required CredentialsCurrently pursuing or recently completed a degree in finance, data science, or related fields; some programming knowledgeBachelor's degree in finance, economics, or related fields; proficiency in data analysis tools
Work EnvironmentInternship setting, often in finance or tech companies, focusing on data pipeline developmentOffice environment, analyzing financial data, creating reports, and supporting decision-making
Employer & Industry UsageUsed by financial institutions, tech firms, and investment companies for data engineering tasksCommon in banks, investment firms, and corporate finance departments for data analysis

The main difference is that an Internship Financial Data Engineer focuses on building and maintaining data infrastructure during an internship, often involving programming and data pipeline work. In contrast, a Financial Data Analyst primarily interprets and reports on financial data to support business decisions. Both roles require a strong understanding of finance and data tools but differ in their core responsibilities and work environment.

What does an internship financial data engineer do?

An Internship Financial Data Engineer assists in building and maintaining data systems that support financial analysis and decision-making. They work with large datasets, help develop data pipelines, and ensure data quality and integrity for financial applications. Interns may use programming languages like Python or SQL, and tools such as databases and cloud platforms, to process and analyze financial data. Their work supports the broader data engineering team and helps improve the efficiency of financial data management within the organization.
What are the most commonly searched types of Financial Data Engineer jobs in Michigan? The most popular types of Financial Data Engineer jobs in Michigan are:

ICT Data Engineer

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 12 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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