Data Engineering Internship

Overview

Are you interested in gaining meaningful work experience in the Home Office of one of the nation's leading specialty retailers? As a Spencer's and Spirit Halloween intern, you'll have the opportunity to enhance your skills, explore your talents, and network with peers and leaders. Our internship program offers a challenging, hands-on experience in a rewarding, supportive, and collaborative environment. Our goal is to prepare you to jump into a career post-graduation.

Internship highlights

• Paid, full-time internship
• Access to all Home Office amenities including our collaborative workspaces, fitness center, and subsidized cafeteria
• Networking opportunities with our Executive Team
• Community events, engagement activities, and professional development workshops
• 30% discount on Spencer's and Spirit Halloween merchandise

Responsibilities

We are looking for a motivated and detail-oriented Data Engineering Intern to support our data engineering and analytics teams. This internship offers hands-on experience in developing and managing data pipelines and collaborating with cross-functional teams to drive business insights. The ideal candidate will be eager to learn, possess foundational knowledge in data systems, and have a passion for data analysis and optimization.

• Assist in developing and managing data pipelines to support business insights related to performance, operational efficiency, and key metrics
• Collaborate with business stakeholders to troubleshoot data-related technical issues and support data and BI teams' operational requirements
• Work with data and analytics experts to enhance functionality, traceability, and cohesion within data systems
• Analyze and understand data footprints, optimizing data usage across the organization
• Support development and architecture teams on data quality initiatives and proof-of-concept (POC) projects

Qualifications

• Available to work 30 hours per week while being on-site a minimum of 2 days per week (Tuesday - Thursday)
• Completion of  junior year preferred and must be enrolled in college for the upcoming semester; graduate students are also encouraged to apply
• Currently pursuing a degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field
• Foundational knowledge of data pipeline design and optimization with a strong interest in big data concepts
• Familiarity with SQL and relational databases; basic experience in query authoring and data analysis
• Exposure to data transformation, data structures, metadata, dependency, and workload management concepts
• Experience or coursework in big data tools (e.g., Hadoop, Spark) and relational and NoSQL databases
• Familiarity with programming languages such as Python or Java
• Strong communication skills and ability to work effectively in a team-oriented environment
• Prior experience or familiarity with Azure and Databricks is a plus

The pay range reflects the potential rate for this role. Individual base pay is determined by various factors such as relevant experience and skills, and the scope and responsibilities of the position.

Pay Range