Senior Data Engineer - job 1 of 2

As a Senior Data Engineer at Sportradar, your primary responsibilities include designing, building, and implementing sophisticated data pipelines for downstream analytics and data science. You'll also lead collaborations with engineering teams to adopt standardized methodologies, drive scalability, and propose improvements to operational processes. Your role is essential in maintaining the efficiency and scale of our complex systems that cater to thousands of sports federations and teams worldwide.

To be successful as a Senior Data Engineer at Sportradar, you should have over 5 years of experience in data engineering or a related software field. Proficiency in Python is essential, along with a demonstrated strength in ETL development and warehousing. Familiarity with container orchestration technologies like Kubernetes is also important. Strong analytical and debugging skills, a solid sense of ownership, and an understanding of the software development lifecycle are key requirements for this role.

In your role as a Senior Data Engineer at Sportradar, you'll leverage a range of tools and technologies, including Python for ETL development, Kubernetes for container orchestration, and potentially Flink for stream processing. Familiarity with data processing tools like NiFi, messaging platforms like Kafka, and a strong grasp of an agile development environment will also benefit you in this position, enhancing your contributions to our sports data pipeline.

Sportradar boasts a collaborative and inclusive culture, particularly for Senior Data Engineers. We value transparency and empowerment, allowing you to shape your workday and career path. Our commitment to work-life balance is evident in our flexible working hours, and we encourage community engagement through groups like Women in Tech and Pride. Joining Sportradar means you’ll experience a vibrant environment where diversity is celebrated and everyone's voice is heard.

The recruitment process for a Senior Data Engineer at Sportradar typically begins with an initial screening interview with our Talent Acquisition Partner. This is followed by two technical interviews—one with the technical team and another with the hiring manager to discuss your solutions and team fit. Finally, you'll receive feedback on your application, and if you're successful, we’ll extend an offer to join our dynamic and innovative team.

In an interview, discuss specific ETL projects you've managed, highlighting the tools you used and the challenges you overcame. Describe how you optimized data flow and performed quality checks to ensure data integrity.

Share your approach to designing scalable data pipelines, focusing on best practices like modular design, robust monitoring, and how you ensure that your architecture can grow with increasing data volumes and complexity.

Explain how collaboration enhances productivity and outcomes. Provide examples of how you’ve worked with other engineering teams to adopt best practices and improve overall systems.

Discuss your systematic approach to debugging, detailing the tools and techniques you use for identifying issues in data pipelines and how you prioritize fixing them while maintaining operation stability.

Describe a significant challenge you faced in your past roles, the steps you took to resolve it, and the outcome, emphasizing your analytical and problem-solving skills.

Talk about your experience using Kubernetes in your previous projects, detailing how it benefitted the performance, scalability, and deployment of your data applications.

Discuss your understanding of data governance and security practices, explaining how you implement them in your work to protect sensitive information and maintain data integrity.

Provide insights into emerging technologies or methodologies in data engineering that you believe will shape the industry, such as serverless computing, machine learning data pipelines, or real-time analytics.

Have a conversation about the methods you use to validate your data transformations, including unit tests and continuous integration practices that help maintain data quality.

Share your passion for sports technology and how you see your role at Sportradar contributing to innovative solutions in sports data. Express your enthusiasm for being part of a leading company in a rapidly evolving industry.