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Internship Startup Data Engineer Jobs in Ohio (NOW HIRING)

Data Platform Engineer

Cleveland, OH · On-site

$23.61 - $70.82/hr

You will have the opportunity to work across several areas of data engineering rather than being ... Equivalent hands-on experience through internships, substantial projects, certifications, or other ...

$80 - $120/hr

Caching, query performance, efficient data flow. You make pragmatic decisions that balance speed ... Engineering Fundamentals: You are confident working with Next.js, React.js, TypeScript, Tailwind ...

Site Digital IT Manager Internship

Lima, OH · On-site

$14.50 - $19.25/hr

Pursuing a Bachelor's degree in Computer Science, Computer Engineering, Data Engineering ... Strong leadership abilities and the capacity to thrive in a fast-paced, startup-like environment.

Showing results 21-40

Internship Startup Data Engineer information

What does an internship startup data engineer do?

An Internship Startup Data Engineer assists in building and maintaining data pipelines and architectures that help startups collect, process, and analyze data. They often work closely with engineers and data scientists to ensure data is accessible and reliable for business needs. Responsibilities may include cleaning and transforming raw data, working with databases, and helping implement data solutions in cloud environments. Interns are expected to learn quickly, adapt to fast-paced changes, and contribute to projects that impact the startup’s growth.

What types of projects and responsibilities can I expect as an internship startup data engineer?

As an Internship Startup Data Engineer, you'll typically work on a variety of hands-on projects such as building data pipelines, cleaning and transforming raw data, and assisting with setting up databases or cloud data solutions. You may collaborate closely with software engineers, data scientists, and product managers to support analytics initiatives or improve data infrastructure. Startups often provide interns with opportunities to take ownership of smaller projects and contribute directly to core products, offering valuable exposure to the full lifecycle of data engineering tasks. Expect a fast-paced environment where adaptability and proactive learning are highly valued.

What are the key skills and qualifications needed to thrive as an internship startup data engineer, and why are they important?

To excel as an Internship Startup Data Engineer, you typically need a background in computer science, statistics, or a related field, along with foundational knowledge in data structures and algorithms. Familiarity with programming languages like Python or SQL, experience with data processing frameworks (such as Pandas or Spark), and version control tools like Git are commonly required. Strong problem-solving abilities, adaptability, and effective communication skills will help you stand out in a dynamic startup environment. These skills are essential for efficiently managing and analyzing data to support rapid product development and informed decision-making in a fast-paced setting.

What is the difference between Internship Startup Data Engineer vs Junior Data Analyst?

AspectInternship Startup Data EngineerJunior Data Analyst
Required CredentialsBasic programming, SQL, data managementStatistical knowledge, Excel, SQL
Work EnvironmentStartup, fast-paced, hands-on projectsCorporate or startup, data reporting and analysis
Employer & Industry UsageTech startups, data-driven companiesVarious industries, marketing, finance, retail
Search & Comparison IntentLearning, entry-level experience, internship opportunitiesData analysis skills, entry-level roles

Internship Startup Data Engineers focus on building data pipelines and managing data infrastructure, often requiring basic programming and SQL skills. Junior Data Analysts primarily analyze data, generate reports, and interpret results. Both roles are entry-level but differ in technical focus and daily tasks, with internships offering hands-on experience in startup environments and analyst roles emphasizing data interpretation.

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

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

What job categories do people searching Internship Startup Data Engineer jobs in Ohio look for?

The top searched job categories for Internship Startup Data Engineer jobs in Ohio are:

What cities in Ohio are hiring for Internship Startup Data Engineer jobs?

Cities in Ohio with the most Internship Startup Data Engineer job openings:

Infographic showing various Internship Startup Data Engineer job openings in Ohio as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Data Platform Engineer

JACK Cleveland Casino LLC

Cleveland, OH

$111K - $133K/yr

Full-time

Posted 14 days ago


Job description

You will have the opportunity to work across several areas of data engineering rather than being limited to one narrow specialty.  This may include data integration, pipeline development, data modeling, quality monitoring, documentation, reporting support, and architecture discovery.  We are more interested in how you approach problems than whether you have already used every technology in our environment.  The right person is dependable, asks thoughtful questions, follows work through to completion, and knows how to use modern AI development tools responsibly and effectively.

Essential Functions

  • Build, maintain, and improve pipelines that move data between operational systems, databases, warehouses, and reporting tools.
  • Help document our existing data environment, including data sources, integrations, transformations, storage, reporting dependencies, and access controls.
  • Support an audit of the current data architecture by investigating how systems connect and identifying potential reliability, scalability, data-quality, security, or maintainability concerns.
  • Work with more experienced team members and business stakeholders to evaluate and prioritize improvements.
  • Develop and maintain reusable data models for reporting, analytics, and operational use.
  • Add testing, monitoring, alerting, logging, and documentation to important data workflows.
  • Investigate failed jobs, inconsistent metrics, and other data issues through structured root-cause analysis.
  • Write readable, maintainable code using source control, code review, automated testing, and repeatable deployment practices.
  • Translate business needs into practical technical solutions with guidance from internal stakeholders.
  • Use AI-assisted development tools to accelerate research, coding, testing, documentation, and troubleshooting.
  • Review and validate AI-generated work rather than accepting it without verification.
  • Learn unfamiliar systems and technologies as needed and share what you discover with the team.

Knowledge, Skills & Abilities 

  • Strong foundational SQL skills and experience working with relational data.
  • Working knowledge of Python, R, or another language used for data processing and automation.
  • Some experience building, modifying, or supporting ETL/ELT pipelines.
  • Familiarity with databases, data warehouses, APIs, scheduled jobs, or cloud-based data services.
  • Basic experience with Git and modern software-development practices.
  • An ability to investigate unfamiliar problems, test assumptions, and communicate findings clearly.
  • A dependable approach to execution, documentation, and follow-through.
  • Genuine curiosity and a willingness to learn technologies outside your current experience.
  • Practical experience using AI coding assistants or language models as part of a development workflow.
  • Good judgment about validating AI-generated code and protecting confidential or sensitive company information. 

Education and Experience

  • Bachelor’s degree in Computer/Data Science or Analytics. In lieu of a degree, comparable professional experience in this discipline.
  • Approximately 1-3 years of relevant professional experience in data engineering, software development, analytics engineering, database development, or a related area.
  • Equivalent hands-on experience through internships, substantial projects, certifications, or other demonstrated work will also be considered.

Additional Preferred Experience

  • Cloud platforms such as Azure, AWS, or Google Cloud.
  • Data platforms such as Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric, or Synapse.
  • Transformation or orchestration tools such as dbt, Airflow, Dagster, Prefect, or Azure Data Factory.
  • Business intelligence tools such as Power BI, Tableau, or Looker.
  • CI/CD, infrastructure as code, containers, or automated deployment processes.
  • Data quality, governance, lineage, cataloging, privacy, or access management.
  • Supporting or documenting an existing data architecture.

Required Certification/License

  • Ability to obtain an OCCC Gaming License, OCCC Sports Gaming License, and an OLC Gaming License