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Entry Level Data Engineering Jobs in Michigan (NOW HIRING)

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Data Engineering information

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How much do entry level data engineering jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for entry level data engineering in Michigan is $17.64, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $19.09 per hour, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Highly experienced data engineers working in senior or specialized roles at large tech companies or financial institutions can earn salaries approaching or exceeding $500,000 annually, often including bonuses and stock options. Such compensation typically requires advanced skills in cloud platforms, big data tools, and extensive industry experience. These roles are rare and usually involve leadership responsibilities or niche expertise.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining data infrastructure, and their skills in programming, database management, and system architecture remain in high demand. AI tools serve as complements that enhance efficiency rather than substitutes for the core responsibilities of data engineers.

What is an Entry Level Data Engineering job?

An Entry Level Data Engineering job involves designing, building, and maintaining data pipelines that collect, process, and store data for analysis. Professionals in this role work with databases, ETL (Extract, Transform, Load) processes, and cloud platforms to ensure data is accessible and reliable. They often collaborate with data analysts and scientists to support business intelligence and machine learning initiatives. Common skills include SQL, Python, and experience with big data tools like Apache Spark or AWS. This role serves as a foundation for more advanced data engineering positions.

What types of projects and tasks can I expect to work on as an Entry Level Data Engineer?

As an Entry Level Data Engineer, you will typically assist with building data pipelines, cleaning and preparing data for analysis, and supporting the migration of data into cloud or on-premises data warehouses. Your daily tasks may include collaborating with data analysts, troubleshooting data quality issues, and learning to automate data flow processes. You’ll often work alongside more senior engineers, gaining exposure to real-world datasets and the software engineering practices that keep data infrastructure running smoothly. This hands-on experience offers a solid foundation for advanced data engineering roles as your career progresses.

Can I get a data engineer job with no experience?

Entry level data engineering roles typically require some knowledge of programming languages like Python or SQL, as well as familiarity with data storage and processing tools such as Hadoop or Spark. While prior experience is often preferred, candidates with relevant internships, certifications, or strong technical skills can sometimes qualify for entry-level positions. Building a solid foundation in data concepts and gaining hands-on experience can improve chances of securing such roles.

What are the key skills and qualifications needed to thrive in the Entry Level Data Engineering position, and why are they important?

To thrive as an Entry Level Data Engineer, you need a solid understanding of programming languages like Python or SQL, basic data modeling, and a relevant degree such as computer science or information technology. Familiarity with ETL tools, cloud platforms like AWS or Azure, and introductory certifications in big data technologies can be advantageous. Attention to detail, strong problem-solving abilities, and effective communication skills are valuable soft skills for this role. These competencies enable you to process and manage large data sets accurately, collaborate with teams, and support data-driven decision-making.

Is data engineering an entry level job?

Data engineering can be an entry level role, especially for those with foundational skills in programming, databases, and cloud platforms. However, many positions require some experience with data pipelines, scripting, and tools like SQL, Python, or Spark, so entry-level candidates should focus on developing these skills and relevant certifications.
What are the most commonly searched types of Data Engineering jobs in Michigan? The most popular types of Data Engineering jobs in Michigan are:
What are popular job titles related to Entry Level Data Engineering jobs in Michigan? For Entry Level Data Engineering jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Engineering jobs in Michigan look for? The top searched job categories for Entry Level Data Engineering jobs in Michigan are:
What cities in Michigan are hiring for Entry Level Data Engineering jobs? Cities in Michigan with the most Entry Level Data Engineering job openings:
Associate Data Engineer - Client Innovation Center (Entry Level)

Associate Data Engineer - Client Innovation Center (Entry Level)

IBM

Lansing, MI • On-site

$14.50 - $19/hr

Full-time

Posted 9 days ago


IBM rating

7.9

Company rating: 7.9 out of 10

Based on 72 frontline employees who took The Breakroom Quiz

100th of 191 rated software companies


Job description

Job Summary:
IBM Consulting Client Innovation Centers (CICs) are environments where technologists build real solutions for clients. The Associate Data Engineer role is entry-level, focusing on supporting the development and maintenance of data pipelines and platforms while collaborating with experienced practitioners.
Responsibilities:
• Support the development and maintenance of data pipelines used for analytics, reporting, and machine learning
• Assist with extracting, transforming, and loading (ETL/ELT) data from multiple sources into data platforms
• Contribute to data cleansing, validation, and transformation activities using Python and SQL
• Help prepare datasets for downstream consumption by analytics and data science teams
• Support batch and, where applicable, near-real-time data processing workflows under guidance
• Collaborate with data engineers, data scientists, and other team members in Agile delivery environments
• Build data engineering skills through training, mentorship, and hands-on delivery experience
• Work with functional and technical team members to help integrate data solutions into client business environments
Qualifications:
Required:
• Strong foundation in computer science fundamentals, including data structures and algorithms
• Strong analytical and problem-solving skills with attention to data quality and reliability
• Comfortable working onsite in a collaborative, team-based environment
• Ability to work effectively in a technology-driven consulting environment where tools, platforms, and client needs evolve over time
• Strong analytical and problem-solving skills, with the ability to approach complex tasks using structured, logical thinking
• Ability to learn new systems and technologies quickly and apply them in a delivery setting
• Proficiency in Python (preferred) or another programming language used for data processing
• Hands-on experience using data manipulation tools such as pandas, NumPy, and SQL, gained through coursework, labs, projects, or internships
• Ability to write clear, maintainable code for data transformation and processing tasks
• Understanding of ETL/ELT concepts and how data moves from source systems to consumption layers
• Familiarity with relational databases and SQL for querying and data manipulation
• Basic understanding of data modeling concepts such as schemas, normalization, or dimensional models
• Exposure to cloud-based data or analytics platforms (e.g., AWS, Azure, or Google Cloud) through coursework, labs, or projects
• Familiarity with core cloud data services such as object storage, databases, or analytics services
• Ability to translate business or functional requirements into technical solutions, with guidance from senior team members
• Comfortable working onsite in a collaborative, team-based environment
• Strong willingness to learn, accept feedback, and continuously improve
• Familiarity with generative AI concepts, including basic modeling approaches, responsible use, and ethical considerations, gained through coursework, projects, or self-study
Preferred:
• Master's Degree
• Exposure to distributed data processing tools such as Apache Spark or PySpark
• Familiarity with modern data warehouse technologies (e.g., Snowflake, Redshift, BigQuery)
• Exposure to streaming or event-based data concepts
• Familiarity with version control tools such as Git
• Basic awareness of how data engineering supports machine learning workflows
Company:
IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions. Founded in 1911, the company is headquartered in Armonk, USA, with a team of 10001+ employees. The company is currently Late Stage.

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About IBM

Sourced by ZipRecruiter

At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Armonk, NY, US

Year founded

1911

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