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Big Data Engineer Intern Jobs in Ohio (NOW HIRING)

Monitise

Senior Cybersecurity Data Engineer

Columbus, OH · On-site

$109K - $182K/yr

You will interface with security Big Data environments, aiding in their design and configuration to ... engineers, database architects, data analysts, and data scientists and will ensure optimal data ...

SVA System Vertrieb Alexander GmbH

$79.78 - $136.77/hr

Als Big Data Consultant (m/w/d) im Bereich IoT entwickeln Sie passgenaue IoT-Lösungen für die ... DevOps-Prinzipien und hoher Sicherheitsstandards * Implementierung der Lösung in der ...

Alexander Thamm GmbH

$82 - $105.42/hr

Konzeptionierung und Aufbau von Big Data / Analytics / AI Plattformen, inklusive DevOps workflows, IaC, CI/CD, IAM und Monitoring & Alerting * Konzeption, Entwicklung und Skalierung von Daten ...

Great American Insurance Group

Data Engineer

Cincinnati, OH · On-site +1

$109K - $131K/yr

We combine a "small company" culture where your ideas will be heard with "big company" expertise to ... Predictive Analytics is seeking a Data Engineer to join our Business Data and Analytics department.

New

Great American Insurance Group

Data Engineer

Cincinnati, OH · On-site

$109K - $131K/yr

We combine a "small company" culture where your ideas will be heard with "big company" expertise to ... Predictive Analytics is seeking a Data Engineer to join our Business Data and Analytics department.

adorsys GmbH & Co. KG

$82 - $105.42/hr

Als Senior Professional Fullstack-Data-Engineer wirst du in unserer Tribe-Organisation stetig ... Practice und pflegen intern eine kollegiale Firmenkultur in einem dynamischen Team. Unsere ...

GHR Healthcare

Senior Data Engineer

Columbus, OH · On-site

$99K - $134K/yr

Experience with big-data or distributed-data technologies such as Spark, Kafka, Hadoop, or NoSQL platforms . * Programming experience with Python, Java, Scala, R , or similar languages. * Experience ...

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Big Data Engineer Intern information

What does a Big Data Engineer Intern do?

A Big Data Engineer Intern assists with designing, building, and maintaining large-scale data processing systems. They often work with technologies such as Hadoop, Spark, and SQL to manage and analyze large datasets. Interns may help develop data pipelines, clean and organize data, and support senior engineers in optimizing data workflows. This role provides hands-on experience in handling big data tools and working on real-world data engineering projects.

What are the key skills and qualifications needed to thrive as a Big Data Engineer Intern?

To thrive as a Big Data Engineer Intern, you need a solid understanding of programming (especially Python, Java, or Scala), data structures, and basic knowledge of distributed computing concepts, typically supported by coursework or relevant projects. Familiarity with big data tools like Hadoop, Spark, and data querying languages such as SQL, as well as exposure to cloud platforms like AWS or Azure, is highly valuable. Strong analytical thinking, problem-solving abilities, and communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills and qualities are crucial for handling large-scale datasets and supporting the development of data-driven solutions within engineering teams.

What are some common challenges a Big Data Engineer Intern might face when working with large datasets?

As a Big Data Engineer Intern, you'll often encounter challenges related to managing the scale and complexity of massive datasets. These can include optimizing data ingestion pipelines for speed and efficiency, troubleshooting data quality issues, and ensuring data privacy and security. Additionally, you may need to quickly learn new tools or frameworks, such as Hadoop or Spark, and collaborate closely with data scientists and engineers to ensure data is structured and accessible for analysis. Developing problem-solving skills and being proactive in seeking help from your team can help you overcome these hurdles.

What is the difference between Big Data Engineer Intern vs Data Engineer?

AspectBig Data Engineer InternData Engineer
CredentialsRelevant coursework, some internshipsBachelor's or master's in CS, experience preferred
Work EnvironmentInternship, learning-focused, entry-level projectsFull-time, professional projects, team collaboration
Industry UsageTech, finance, healthcare, startupsSame industries, more responsibility
Search & Comparison IntentEntry-level, internship opportunitiesCareer advancement, full-time roles

The main difference between a Big Data Engineer Intern and a Data Engineer is experience level and responsibility. Interns are typically students or early learners gaining exposure, while Data Engineers are full-time professionals managing complex data systems. Internships serve as stepping stones toward full-time data engineering careers.

What cities in Ohio are hiring for Big Data Engineer Intern jobs?

Cities in Ohio with the most Big Data Engineer Intern job openings:

Big Data Engineer Intern jobs near you

Business Analyst / Data Engineer II_ Cincinnati, OH

campus4tech

Cincinnati, OH • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Role: Business Analyst / Data Engineer II
Location: Cincinnati, OH. ROLE IS 100% ON-SITE
Duration: Till 12/31/25, should extend out long term.
Job Details:
This is heavier on the Business Analyst side. Someone with strong communication skills- they want someone communicating more, asking more questions, raising concerns, and buying in to the product owner. Looking for someone to help with requirements, but someone that is also very strong in their testing skills. A candidate that can take the requirements and use them create user stores and test plans to confirm that the user needs are being met during UAT and even in PROD with working on production issues.
MUST HAVE SKILLS
  • Power BI 3-4 years
  • Analytical
  • SQL, 3-5 years
  • Strong Communications Skills
  • Able to run meetings
  • Problem Solving and Critical Thinking

NICE TO HAVE SKILLS/Experience
  • DataStage
  • Dataiku
  • AFS system application (AFS Level III or Vision)

GENERAL FUNCTION:
  • The data engineer/business analyst designs solutions that help the bank manage, secure, and generate value from its data.
  • The person in this role creates scalable and reusable solutions for gathering, collecting, storing, processing, and serving data on both small and very large (i.e. Big Data) scales.
  • These solutions can include on-premises and cloud-based data platforms, and solutions in any of the following domains ETL, business intelligence, analytics, persistence (relational, NoSQL, data lakes), search, messaging, data warehousing, stream processing, and machine learning.
  • Responsible and accountable for risk by openly exchanging ideas and opinions, elevating concerns, and personally following policies and procedures as defined.
  • Accountable for always doing the right thing for customers and colleagues and ensures that actions and behaviors drive a positive customer experience. While operating within the Bank's risk appetite, achieves results by consistently identifying, assessing, managing, monitoring, and reporting risks of all types.

ESSENTIAL DUTIES AND RESPONSIBILITIES:
  • Ability to work independently, meet with line of business and ask questions to gain an understanding of their requirements. Critical thinking skills would then take those requirements and break them down into the lowest level what so that functional design can be completed.
  • Ability to collaborate with team members that are more technical and communicate those requirements in a way that allows the tech team members to understand them and determine the proper technical design.
  • Ability to create clear and complete Test Acceptance criteria and execute the testing to ensure accurate output during Unit and UAT.
  • Capable of creating and executing SQL scripts for ETL/data testing.
  • Conduct research and Development based on current trends and technologies related to the banking industry, data engineering and architecture, data security, and related topics.
  • Ability to build CI/CD pipelines, Self-service Build tools, and automated deployment processes.
  • Evaluate software products and provide documented recommendations as needed.
  • Provide Support and troubleshooting for data platforms. Must be willing to Provide escalated on-call Support for complicated and/or critical incidents.
  • Plan and work on internal projects as needed, including legacy system replacement, Monitoring and analytics improvements, tool Development, and technical documentation.
  • Provide guidance and mentoring for other team members.
  • Manage and prioritize multiple assignments.

MINIMUM KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:
  • Bachelor's degree in Computer Science/Information Systems or equivalent combination of education and experience.
  • Strong communication skills- Must be able to communicate ideas both verbally and in writing to management, business and IT sponsors, and technical resources in language that is appropriate for each group.
  • Excellent analytical and problem-solving skills when resolving data related issues or designing new solutions
  • Technical skills - SQL (3-5 years of experience), DataStage (ETL), DBT, Snowflake, Python
  • Conceptual understanding of one or more of the following disciplines preferred big data technologies and distributions, metadata management products, commercial ETL tools, Data Visualization and reporting tools, data warehousing, SQL, data testing, major cloud, or rest API design and development.
  • Experienced in SDLC and can assist in Project Management. Able to understand release management protocols and manage important tasks for implementation.

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