Data Engineer I

JOIN THE BEST TEAM IN SPORT & SPIRIT At Varsity Brands, we believe every student deserves the opportunity to succeed and every educator wants to make a difference. It takes a team to make a real impact, and through our two divisions - BSN SPORTS and Varsity Spirit - and our network of 6,000+ employees and independent representatives, we are proud to partner with a wide range of educational institutions and club and professional sports to transform the student journey in SPORT and SPIRIT. LOCATION: 14460 Varsity Brands Way Farmers Branch, Tx - Varsity Brands HQ WORK TYPE: Onsite HOW YOU WILL MAKE AN IMPACT: 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. Impact of the Role Contributes to delivery of trusted data pipelines and data products supporting analytics, reporting, and AI initiatives Builds foundational engineering capabilities supporting a scalable, cloud‑based enterprise data platform Improves data accessibility, consistency, and quality across enterprise systems Supports the organization’s transition from fragmented data sources to governed, reusable enterprise data assets WHAT YOU WILL DO: 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 Key Performance Indicators Quality and reliability of delivered data pipelines and transformations Timely completion of assigned engineering work Accuracy and quality of data supporting downstream consumers Ability to troubleshoot and resolve issues with increasing independence Consistent adoption of engineering standards, documentation, and development practices Demonstrated growth in technical capability and understanding of the enterprise data platform QUALIFICATIONS: Knowledge, Skills, Abilities Technical Knowledge 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 Technical Skills 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 Cognitive & Problem‑Solving Abilities Applies logical reasoning to solve defined technical problems Exercises independent judgment in selecting appr #J-18808-Ljbffr