Data Engineer I
About The Position
Varsity Brands is building a modern enterprise data platform that powers analytics, reporting, artificial intelligence, and data-driven decision-making across the organization. The platform brings together data from enterprise applications, digital products, manufacturing, supply chain, and customer systems into trusted, scalable, and governed data products and platform capabilities that enable analytics, operational intelligence, and AI. The Data Engineer I (DE I) is an entry-level engineering position responsible for contributing to the development of the enterprise data platform. This role applies foundational data engineering knowledge and exercises independent judgment in executing assigned work, including selecting appropriate approaches within established engineering standards to develop, test, and maintain data pipelines, transformations, and data products. This role is designed to develop the next generation of data engineers who will help build the trusted data foundation supporting Varsity Brands' analytics, operational intelligence, and AI strategy.
Requirements
- Foundational understanding of data engineering principles and modern data platforms
- Basic Understanding of relational databases, data modeling, and data integration concepts
- Familiarity with cloud-based data platforms and modern data engineering environments
- Basic understanding of data governance, data quality, and metadata concepts
- Ability to develop and test SQL queries and data transformations
- Foundational programming skills using Python or a comparable language
- Familiarity with modern data engineering tools and technologies, including: Modern cloud data platforms (Snowflake preferred), SQL, Python for data engineering and automation, Git-based version control, ETL/ELT concepts, Basic understanding of CI/CD and automated testing concepts
- Applies logical reasoning to solve defined technical problems
- Exercises independent judgment in selecting approaches within established engineering guidelines
- Identifies data quality and pipeline issues and escalates appropriately when needed
- Demonstrates attention to detail and commitment to producing accurate, reliable data
- Communicates effectively within cross-functional team environments
- Collaborates with engineers, analysts, architects, and business stakeholders
- Actively participates in team discussions and engineering ceremonies
- Incorporates coaching and feedback to improve technical capability
- Demonstrates curiosity and willingness to learn emerging data technologies and engineering practices
- Adapts to evolving cloud platforms, tools, and business priorities
- Builds understanding of enterprise data architecture and modern data engineering patterns
- Identifies opportunities to automate, simplify, and improve engineering processes
- Seeks opportunities to reduce technical debt and improve operational excellence
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, or a related technical discipline; or equivalent combination of education and experience
- 0 – 2 years of relevant experience, including internships, academic projects, or early career experience in data engineering, software engineering, analytics engineering, or related technical disciplines
- Foundational knowledge of SQL and relational databases
Nice To Haves
- Exposure to cloud data platforms such as Snowflake
- Exposure to Python, dbt, or comparable data transformation tools
- Familiarity with Git, CI/CD, and Agile software development practices
- Experience working with modern data visualization or analytics platforms through coursework, internships, or projects
Responsibilities
- Develop, test, and maintain data pipelines, transformations, and data integration processes using established engineering standards
- Assist in building and maintaining data products that support analytics, reporting, and AI use cases
- Write, optimize, and troubleshoot SQL queries and data transformations
- Participate in code reviews and incorporate feedback to improve quality, maintainability, and performance
- Troubleshoot lower-complexity data pipeline and data quality issues, exercising sound judgment to identify appropriate solutions and escalating when necessary
- Collaborate with Data Engineering, Analytics Engineering, Business Intelligence, Enterprise Architecture, Application Engineering, and business stakeholders to deliver reliable data solutions
- Follow established engineering practices for testing, version control, CI/CD, security, and documentation
- Contribute to data quality, observability, and monitoring activities to improve platform reliability
- Document data pipelines, transformation logic, metadata, and engineering processes to support knowledge sharing and operational continuity
- Develop working knowledge of enterprise data architecture, cloud data platforms, orchestration frameworks, and engineering patterns to support future growth into independent ownership
Benefits
- Comprehensive Health Care Benefits
- HSA Employer Contribution/ FSA Opportunities
- Wellbeing Program
- 401(k) plan with company matching
- Company paid Life, AD&D, and Short-Term Disability
- Generous My Time Off & Paid Holidays
- Varsity Brands Ownership Program
- Employee Resource Groups
- Access to Financial Coaching and member-owned Credit Union
- St. Jude Partnership & Volunteer Opportunities
- Employee Perks including discounts on personal apparel and equipment!
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
