Hybrid Data Engineering & Science Internship (Remote)

Park National Bank; Newark (OH); Hybrid; USD 25,000 - 39,000; Full time

Job summary

Park National Bank is seeking a Data Engineering/Data Science Summer Internship in Newark, OH with a hybrid work arrangement (1 day on-site, 4 days remote). Typical hours are 40 per week, and transportation to headquarters is required.

The internship focuses on building data semantic models, designing data pipelines with DBT, and collaborating with data scientists and business stakeholders to translate requirements into robust technical solutions.

Qualifications

• 2-year associate degree in IT/CS or related discipline required.
• SQL experience required; scripting ability.
• Basic programming experience in reporting software and data workflows.

Responsibilities

• Builds and maintains data semantic models to support analytics and BI use cases.
• Designs, develops, and manages data pipelines using DBT for data transformation and delivery.
• Collaborates with data scientists, engineers, and stakeholders to translate requirements into technical solutions.
• Builds cross-functional relationships to support data initiatives.
• Supports developing and optimizing scripts and data workflows integrated into banking applications.
• Demonstrates proficiency in SQL/Python; experience with Tableau or Power BI for validation and insights.
• Transforms raw data into structured formats for analysis and AI agents.
• Ability to pick up NLP-based coding in Snowflake and DBT.

Skills

SQL

Python

Data modeling

BI tooling

Education

Associate degree in IT/CS

High School Diploma

Tools

DBT

Snowflake

Tableau

Power BI

Job description

Park National Bank is seeking a Data Engineering/Data Science Summer Internship in Newark, OH with a hybrid work arrangement (1 day on-site, 4 days remote). Typical hours are 40 per week, and transportation to headquarters is required.

The internship focuses on building data semantic models, designing data pipelines with DBT, and collaborating with data scientists and business stakeholders to translate requirements into robust technical solutions.