Staff Data Engineer

About this role

PENN Entertainment, Inc. is North America’s leading provider of integrated entertainment, sports content, and casino gaming experiences. From casinos and racetracks to online gaming, sports betting and entertainment content, we deliver the experiences people want, how and where they want them. We’re always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether it’s through Hollywood Casino, theScore Bet Sportsbook, or theScore media app, we’re excited to push the boundaries of what’s possible. These state-of-the-art platforms are powered by proprietary in-house technology, a key component of PENN’s omnichannel gaming and entertainment strategy. When you join PENN Entertainment’s digital team, you’ll not only work on these cutting-edge platforms through theScore and PENN Interactive, but you’ll also be part of a company that truly cares about your career growth. We’re committed to supporting you as you expand your skills and explore new opportunities. With locations throughout North America, you can build a future at PENN Entertainment wherever you are. If you want to challenge conventions in gaming, media and entertainment, we want to talk to you. About the Role & Team As a Staff Data Engineer, you’ll partner closely with Data Services, Analytics Engineering, Product, and Business stakeholders to design and deliver scalable, reliable, and high-quality data solutions. You will play a key technical leadership role, helping shape the architecture, standards, and future direction of our data platform. The ideal candidate combines deep technical expertise with strong communication skills, a passion for data, and an interest in sports, gaming, and digital products. About the Work As a key member of our team, you will: Collaborate with business stakeholders to identify and prioritize data-driven opportunities and initiatives. Design, build, and maintain scalable data pipelines supporting analytics, reporting, product, and operational use cases. Develop, test, and optimize dbt models following data modeling best practices. Manage and support orchestration platforms including Airflow and exposure to Dagster. Design and implement dimensional, semantic, and analytical data models to support self-service analytics and business intelligence. Drive data architecture decisions and establish engineering standards and best practices across the organization. Partner with data engineers and platform teams to improve the reliability, scalability, and performance of our data ecosystem. Develop and maintain data quality frameworks, testing strategies, and observability solutions to ensure trusted data assets. Support governance initiatives through documentation, metadata management, lineage, and data ownership practices. Complete complex analyses and provide actionable recommendations to business stakeholders. Oversee team analysis to ensure data accuracy, consistency, and business relevance. Champion adoption of data exploration and self-service analytics tools across the organization. Lead technical design reviews and provide mentorship through code reviews, architectural guidance, and knowledge sharing. Support data engineer hiring, onboarding, mentoring, and continued professional development. Participate in incident response, root cause analysis, and continuous improvement initiatives for critical data platform issues. Other duties as required. About the You Bachelor’s degree in Computer Science, Data Engineering, Statistics, Information Systems, Business, or a related field. 8+ years of experience in data engineering, analytics engineering, or a related discipline. Hands-on expertise with BigQuery, dbt, Airflow, Python, SQL, and modern cloud data platforms. Strong understanding of data warehousing concepts, ETL/ELT design patterns, and dimensional modeling. Experience building and optimizing scalable data transformation pipelines in cloud environments. Experience