Senior Data Engineer

Summary

Join PENN Entertainment's theScore Data Engineering team and contribute to the development and maintenance of high-quality, sustainable data-driven solutions. Collaborate with Data Science and other engineering teams to build data pipelines and infrastructure. Oversee the design and maintenance of data pipelines, ensuring performance, scalability, and reliability. Maintain and expand existing systems, tooling, and infrastructure, including streaming pipelines. The ideal candidate possesses a strong background in data engineering, database management, and computer science, along with extensive experience in relevant technologies. PENN Entertainment offers a competitive compensation package and a supportive work environment.

Requirements

• 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, Argo workflows
• Experience with Docker and Kubernetes
• Experience building out a scalable infrastructure to fit the needs of a growing company
• Experience with BigQuery, GCP or other SQL-based data warehouses
• Experience with at least one major cloud platform (GCP, AWS, Azure)
• Experience with testing frameworks such as Pytest, PyUnit, Junit, Mockito
• Experience with RESTful API development
• Strong organization and collaboration skills
• Excellent written and oral communications skills

Responsibilities

• Collaborate with Data Science, 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
• Maintain streaming pipelines that ingest near-real time data
• Other duties as required

Preferred Qualifications

Experience working with Data Scientists or deploying machine learning models

Benefits

• Competitive compensation package
• Fun, relaxed work environment
• Education and conference reimbursements
• Parental leave top up
• Opportunities for career progression and mentoring others