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Data Engineer, Services

Penn Interactive (PI) is an interactive gaming company headquartered in Philadelphia. PI is the digital arm of PENN Entertainment (NASDAQ: PENN), the largest regional casino operator in the U.S.). Our mission is to challenge the norms of the gaming industry by building an immersive interactive gaming experience that is responsible, innovative, and fun. We are committed to helping our team members grow and succeed. We believe that hiring talented individuals that love what they do will help us win!About the Role & TeamAs part of the theScore 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 WorkAs a key member of our Data Engineering team you will:Collaborate with Data Science, Reporting, Analytics and other engineering teams to build data pipelines, infrastructure and tooling to support business initiativesOversee the design and maintenance of data pipelines and contribute to the continual enhancement of the data engineering architectureCollaborate with the team to meet performance, scalability, and reliability goalsWrite out tests and thorough documentation for processes and toolingAdapt to working with new technologies and frameworks, sometimes headlining the investigation into their usefulness to the teamMaintain and expand existing systems, tooling and infrastructureMaintain streaming pipelines that ingest near-real time dataTake ownership of projects, plan and collaborate with other members of the Analytics and Reporting teams or others within the companyOther duties as requiredAbout You A solid foundation in computer science, with strong competencies in data structures, distributed systems, algorithms and software design5+ years of experience in data or software engineeringStrong knowledge of Python or JavaStrong knowledge of relational databases and SQLExperience with Docker and KubernetesExperience with streaming technologies, such as Kafka, Spark, Flink and BeamExperience building out a scalable infrastructure to fit the needs of a growing companyExperience with BigQuery, Redshift or other SQL-based data warehousesExperience with at least one major cloud platform (GCP, AWS, Azure)Experience with testing frameworks such as Pytest, PyUnit, Junit, MockitoExperience with RESTful API developmentStrong organization and collaboration skillsExcellent written and oral communications skillsNICE TO HAVE: Experience working with Data Scientists or deploying machine learning modelsWhat We Offer Competitive compensation packageFun, relaxed work environmentEducation and conference reimbursements.Parental leave top upOpportunities for career progression and mentoring others• LI-Hybrid• LI-RemoteCheck out our LinkedIn page!Recently being recognized as a top workplace in the United States, we believe people work their best when they can be themselves. We are looking for hungry, innovative thinkers to help us challenge the status quo of the gaming industry. Diversity, equity, and inclusion are vital to all of our processes, programs, and structures. Your story, who you are, and your experience matter here. Penn Interactive
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Benjie Levy
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What You Should Know About Data Engineer, Services, Penn Interactive

At Penn Interactive (PI), we’re on a mission to transform the gaming industry, and we’re looking for a passionate Data Engineer to join our vibrant team! Located in State Line, PA, PI is the digital branch of PENN Entertainment, the largest regional casino operator in the U.S. As a key player in our Data Engineering team, you’ll collaborate with brilliant Data Engineers, Analysts, and Data Scientists who are dedicated to crafting high-quality data-driven solutions. Your main focus will be to develop and maintain robust data pipelines and tools that will enhance user experience and optimize profitability. Whether it’s designing scalable infrastructure or tackling real-time data ingestion, your expertise will ensure our operations run smoothly. You’ll dive deep into technologies like Python, Java, Docker, and Kubernetes, while also exploring exciting innovations like Kafka and Spark. Plus, you’ll get to apply your computer science skills to create cutting-edge data architectures. If you have a knack for problem-solving and a love for data—coupled with an interest in sports or eSports—you’ll fit right in! Join us at Penn Interactive, where you’ll work in a fun, relaxed environment that fosters growth and innovation. Here, your voice matters, and together, we’ll challenge the gaming industry's norms while shaping the future of interactive gaming!

Frequently Asked Questions (FAQs) for Data Engineer, Services Role at Penn Interactive
What are the responsibilities of a Data Engineer at Penn Interactive?

As a Data Engineer at Penn Interactive, you will be responsible for collaborating with Data Science, Reporting, Analytics, and engineering teams to design and maintain efficient data pipelines and infrastructure. You'll oversee the continual enhancement of our data architecture and adapt new technologies to improve workflows. Additionally, your duties will include maintaining streaming pipelines, taking ownership of projects, and ensuring high performance and reliability across all systems.

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What qualifications do I need to become a Data Engineer at Penn Interactive?

To become a Data Engineer at Penn Interactive, you should have a solid foundation in computer science, complemented by at least 5 years of experience in data or software engineering. Strong knowledge of languages like Python or Java is essential, along with solid skills in SQL and relational databases. Familiarity with tools such as Docker, Kubernetes, and streaming technologies like Kafka and Spark will set you up for success in this role.

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Is experience in sports or eSports important for the Data Engineer position at Penn Interactive?

While not mandatory, having an interest in professional sports, betting, or eSports can be beneficial for a Data Engineer position at Penn Interactive. This knowledge can help you understand the data landscape better and make informed decisions that align with our business initiatives centered around gaming and user engagement.

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What technologies will I work with as a Data Engineer at Penn Interactive?

As a Data Engineer at Penn Interactive, you will work with a variety of advanced technologies including Python, Java, Docker, and Kubernetes. You'll also have the opportunity to engage with streaming technologies like Kafka, Spark, and Flink, as well as SQL-based data warehouses like BigQuery and Redshift, all while collaborating with cutting-edge data science and analytics teams.

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What kind of work environment can I expect at Penn Interactive?

At Penn Interactive, you can expect a fun and relaxed work environment that promotes creativity and collaboration. Recently recognized as a top workplace in the U.S., we value diversity, equity, and inclusion, and we believe that employees thrive when they are free to be themselves. Our culture encourages innovation, mentorship, and continuous learning.

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Common Interview Questions for Data Engineer, Services
Can you explain your experience with data pipelines?

When answering this question, emphasize specific projects you've worked on involving data pipelines. Highlight the technologies you utilized, the challenges faced, and how you ensured their efficiency and reliability. Be prepared to discuss the architecture of the pipelines you've built and any improvements or optimizations you’ve implemented.

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What tools do you prefer for data engineering and why?

Discuss the tools you are most experienced with, such as Python, SQL, and Kafka. Explain your rationale for preferring these tools based on their performance, ease of use, and compatibility with your workflow. Be honest about your experiences using them and any challenges you’ve overcome.

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How do you ensure data quality and integrity in your projects?

To ensure data quality and integrity, discuss your approaches to data validation and testing. Mention any testing frameworks you're familiar with, such as Pytest or Junit, and provide examples of how you've identified and resolved data discrepancies in past projects.

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Describe a challenging problem you faced as a Data Engineer and how you solved it.

Share a specific example of a difficult challenge, particularly one related to scaling, data integrity, or pipeline performance. Explain your thought process, the steps taken to resolve the issue, and the outcome. This showcases your problem-solving skills and persistence.

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How do you stay current with new technologies in data engineering?

Discuss your methods for staying updated, such as following industry blogs, attending webinars, or participating in online forums. Highlight specific resources that have helped you learn about new trends and tools so you can adapt them in your work.

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Can you discuss a project where you collaborated with data scientists?

When discussing collaborative projects with data scientists, emphasize your role in providing data insights and infrastructure support. Outline the project scope, your contributions, and how your collaboration enhanced the project outcomes.

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What database technologies are you familiar with?

Make sure to mention specific database technologies like MySQL, PostgreSQL, or Redshift, and provide examples from your experience. Share your perspectives on choosing the right database for different tasks, focusing on performance and scalability.

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How do you handle near-real-time data ingestion?

Discuss your experiences with streaming technologies like Kafka or Spark, emphasizing the challenges and best practices in managing real-time data ingestion. Your answer could include specific tools or techniques you've used to optimize this process.

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What is your approach to documentation in data engineering?

In your answer, highlight the importance of clear and thorough documentation. Discuss how it facilitates understanding and collaboration within a team. Mention specific tools or formats you use to document your processes and workflows.

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Why do you want to work as a Data Engineer at Penn Interactive?

This is an opportunity to align your values and aspirations with the company’s mission. Share how your skills and interests in data engineering connect with Penn Interactive's focus on innovative and fun gaming experiences. Show your enthusiasm for the role and how you can contribute to the team.

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Mission: To challenge the norms of the gaming industry by building an immersive interactive gaming experience that is responsible, innovative, and fun. Willingness to succeed and win – always challenge the status quo and solve problems that have ...

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Full-time, hybrid
DATE POSTED
December 17, 2024

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