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 ESPN BET, Hollywood Casino, theScore Bet Sportsbook & Casino, 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 part of the Data Engineering team, you will be working with a team of smart, friendly, and dedicated Data Engineers, Analysts, and Data Scientists determined to develop high-quality and sustainable data-driven solutions to improve profitability, growth and the user experience. You'll work hand in hand with the ML, Analytics, and Reporting teams to develop and maintain data pipelines & internally developed tools to improve workflows and automate processes wherever possible. The ideal candidate has a passion for data, a strong background in data engineering, database management & computer science. An interest in professional sports, betting and/or eSports is a plus. About the Work Collaborate with Data Science, Reporting, Analytics and other engineering teams to build data pipelines, infrastructure and tooling to support business initiatives Oversee the design and maintenance of data pipelines and contribute to the continual enhancement of the data engineering architecture Collaborate with the team to meet performance, scalability, and reliability goals Write out tests and thorough documentation for processes and tooling Adapt to working with new technologies and frameworks, sometimes headlining the investigation into their usefulness to the team Maintain and expand existing systems, tooling and infrastructure Develop and maintain streaming pipelines that ingest near-real time data for teams across the enterprise Take ownership of projects, plan and collaborate with other members of the Analytics and Reporting teams or others within the company Provide on-call support for workloads critical to the organization Other duties as required About You A solid foundation in computer science, with strong competencies in data structures, distributed systems, algorithms and software design 7+ years of experience in data or software engineering Strong knowledge of Python Strong knowledge of relational databases and SQL Strong knowledge of streaming technologies, such as Kafka, Spark, Flink and Beam Experience with Docker and Kubernetes Experience building out a scalable infrastructure to fit the needs of a growing company Experience with Google Cloud Platform Experience with testing frameworks such as Pytest Strong organization and collaboration skills Excellent written and oral communications skills What We Offer Competitive compensation package Fun, relaxed work environment Education and conference reimbursements. Parental leave top up Opportunities for career progression and mentoring others #LI-REMOTE #LI-REMOTE Candidates residing in Ontario requiring special accommodation can email accessibilityoffice@thescore.com theScore is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability or age. Save