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Entry Level Ai Data Engineer Jobs in Ohio (NOW HIRING)

BMW Group

$26/hr

Work on AI/Data Science and/or Innovation use case. * Showcase progress and successes to business ... Knowledge of Python programming, UNIX, Web Frameworks (HTML, CSS, React.JS, Django, etc.) , UI/UX, ...

Flexjet

AI Engineer

Cleveland, OH · On-site

You will work closely with data scientists, software engineers, and product teams to build scalable AI systems that drive business value and enhance user experiences. DUTIES & RESPONSIBILITIES Design ...

Flexjet

AI Engineer

Cleveland, OH · On-site

You will work closely with data scientists, software engineers, and product teams to build scalable AI systems that drive business value and enhance user experiences. DUTIES & RESPONSIBILITIES Design ...

Flexjet

AI Engineer

Cleveland, OH · On-site

You will work closely with data scientists, software engineers, and product teams to build scalable AI systems that drive business value and enhance user experiences. DUTIES & RESPONSIBILITIES · ...

Flexjet

AI Engineer

Cleveland, OH · On-site

You will work closely with data scientists, software engineers, and product teams to build scalable AI systems that drive business value and enhance user experiences. Responsibilities : • Design ...

Sogeti

Entry Level Technology Consultant

Columbus, OH · On-site

As an Entry-Level Technology Consultant at Sogeti , you wi ll join one of our core practices based ... quality engineering, cloud and application development, all driven by AI, data and automation.

CACI

AI Full Stack Developer

Dayton, OH · On-site

$63K - $129K/yr

Job Title: AI Full Stack Developer Job Category: Information Technology Time Type: Full time ... Data & Database Architecture: Strong experience with relational databases (e.g., PostgreSQL) and ...

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Entry Level Ai Data Engineer information

What is an entry level AI data engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an entry level AI data engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

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

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

How to get into entry level AI data engineering?

To enter an entry-level AI data engineering role, develop skills in programming languages like Python and SQL, understand data pipelines and databases, and gain experience with cloud platforms such as AWS or Azure. Completing relevant certifications or courses in data engineering and machine learning can also improve job prospects.

What are the most commonly searched types of Ai Data Engineer jobs in Ohio?

The most popular types of Ai Data Engineer jobs in Ohio are:

What are popular job titles related to Entry Level Ai Data Engineer jobs in Ohio?

For Entry Level Ai Data Engineer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Engineer jobs in Ohio look for?

The top searched job categories for Entry Level Ai Data Engineer jobs in Ohio are:

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Entry Level Ai Data Engineer jobs near you
Infographic showing various Entry Level Ai Data Engineer job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Associate Data/ Metadata Analyst

OCLC, Inc.

Dublin, OH • On-site

Full-time

Medical, Retirement

Posted 24 days ago

Key responsibilities

  • Manage the lifecycle of bibliographic and holdings data, including ingestion, normalization, enrichment, and matching.

  • Assess data quality by profiling incoming data, identifying issues, and troubleshooting data quality problems.

  • Support technical workflows by applying scripts, monitoring data quality through dashboards, and utilizing AI-assisted tools for record matching and field mapping.

Job description

Together we make breakthroughs possible.
At OCLC, we build technology with a purpose: to connect libraries and make knowledge accessible worldwide, because we believe that what is known must be shared. Our teams work with complex global datasets, AI and machine learning, hybrid cloud solutions, and other technologies that connect people and organizations to the information they need. We value the power of unique perspectives and experiences to unlock innovation. At OCLC, your ideas matter, whether you have two years of experience or 20. You'll learn, create, and problem-solve with technologists, product developers, librarians, researchers, marketing pros, and support teams around the world.
Why join OCLC?
OCLC is consistently recognized as a best place to work by several independent programs. We recognize and reward people and results with a comprehensive Total Rewards package. This means competitive compensation that reflects your unique contributions-performance, experience, and skills-along with exceptional benefits, including best-in-class health coverage, retirement plans with generous company contributions, and a commitment to your overall well-being.
  • We know the best ideas don't always happen at a desk. Take a walking meeting around our 100-acre campus or enjoy lunch on the patio. We're committed to your success-both personally and professionally. Hybrid work environment: For many roles, three days a week on-site, with occasional additional days based on business needs.
  • Free use of our on-site fitness center, gym sports, group exercise classes, and game room
  • Onsite catering and cafeteria subsidized by OCLC
  • Health and wellness events
  • Work environments with individual and team spaces and the latest technology tools
  • Paid parental leave and adoption assistance
  • Tuition reimbursement and Public Service Loan Forgiveness eligibility
  • Company-subsidized pricing on local tickets and memberships

Join us in transforming how people everywhere access information and be part of a mission-driven team that makes a global impact.
The job details are as follows:
The Associate Data Analyst/Metadata Analyst manages the lifecycle of bibliographic and holdings data, ensuring accuracy and integrity through evaluation, transformation, and maintenance. This entry-level role combines metadata expertise with developing technical skills in scripting, automation, and AI-assisted workflows. Working under regular supervision, the Associate will transition from executing well-defined tasks to taking ownership of complex data projects. This is an opportunity to develop expertise at the intersection of library data, modern data engineering, and emerging AI - in a team that invests in the growth of its people.
Responsibilities:
Data Operations & Quality
  • Data Lifecycle Management: Perform data ingest, normalization, enrichment, and matching according to established standards (e.g., MARC, KBART).
  • Quality Assessment: Profile incoming data to identify and resolve structural issues, encoding errors, and tagging discrepancies.
  • Troubleshooting: Investigate and resolve data quality issues, escalating complex problems to senior staff as needed.
  • Vendor Communication: Coordinate with external data providers and partner institutions regarding routine data specifications and quality issues.
Technical Solutions & Automation
  • Pipeline Support: Apply existing scripts and automated workflows to process data; identify inefficiencies and suggest process improvements.
  • Data Visualization: Use and interpret dashboards (e.g., Power BI) to monitor data quality trends and communicate findings.
  • AI Integration: Utilize AI-assisted tools for record matching and field mapping; contribute structured feedback that helps improve AI model accuracy over time.
Collaboration & Documentation
  • Knowledge Management: Document data source profiles, processing decisions, and technical workflows to ensure team-wide knowledge sharing.
  • Team Support: Execute foundational tasks to support senior analysts and participate in platform improvement projects.

Minimum Required Knowledge, Skills and Experience:
  • Bachelor's degree in computer science, math, statistics, or related field and internship experience with data analysis or creation of library data.
  • Entry-level analytical and communication skills, with attention to data quality while working under regular supervision.

Preferred Knowledge, Skills and Experience:
  • Metadata Standards: Foundational knowledge of MARC, Dublin Core, KBART, or BIBFRAME.
  • Technical Tools: Exposure to scripting languages (Python, SQL, or XSLT) and data transfer protocols (SFTP, APIs, or AWS S3).
  • Data Platforms: Conceptual familiarity with cloud data stores (e.g., Snowflake) and visualization tools (e.g., Power BI, Streamlit).
  • Emerging Tech: Interest in applying AI and linked data concepts (e.g., Schema.org) to library data challenges.

Working Conditions: Normal office environment.
ADA/EAA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.

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