Data Engineering Intern — Build Analytics Pipelines

Live Oak Bank; Wilmington (NC); On-site; USD 26,000 - 44,000; Full time

Job summary

Live Oak Bank is seeking a Data Engineer Intern for a 10-week Summer Internship program at our headquarters in Wilmington, NC. This onsite role offers hands-on experience building data pipelines and analytics platforms within a scaled agile team.

You''ll work with Finance, Compliance, Lending, and Deposits to deliver high-quality data sources, learn ETL/ELT patterns, and help document designs and standards that empower product teams with trusted data.

Qualifications

• 2–6 months hands-on data modeling and transformation experience.
• 2–6 months experience with AWS-based data warehouse tech like Redshift, Databricks, Snowflake.
• 2–6 months experience with orchestration tools such as Airflow or AWS Glue.
• Basic understanding of event-driven/streaming workflows with Kafka or Spark.
• Ability to work in a team and follow Agile/scrum processes.

Responsibilities

• Define and create data ingestion patterns, pipelines, and standards for self-service analytics across bank domains.
• Hands-on contributor building data products from source to target ingestion and data marts.
• Build role-based access controls and data platform management processes for growth and scalability.
• Refine and prioritize work to support analytics tools and processes.
• Document designs, standards, and user guides for Product teams.

Skills

Data modeling

SQL

Problem solving

Communication

Tools

AWS Redshift

Databricks

Snowflake

Airflow

AWS Glue

Kafka

Spark

Git

Job description

Live Oak Bank is seeking a Data Engineer Intern for a 10-week Summer Internship program at our headquarters in Wilmington, NC. This onsite role offers hands-on experience building data pipelines and analytics platforms within a scaled agile team.

You''ll work with Finance, Compliance, Lending, and Deposits to deliver high-quality data sources, learn ETL/ELT patterns, and help document designs and standards that empower product teams with trusted data.