// Open Role at Sportradar
Join Sportradar's Ads Analytics team as a Senior Data Engineer, owning complex data projects from architecture to delivery. You'll build scalable pipelines, optimize performance, and leverage AWS and Spark to transform terabytes of advertising data into actionable insights for the sports technology industry.
We’re the world’s leading sports technology company, at the intersection between sports, media, and betting. More than 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries rely on our know-how and technology to boost their business.
ABOUT US:
The Ads Analytics team is the backbone of our advertising intelligence platform, processing terabytes of data daily from programmatic, social, and search advertising channels. We build end-to-end solutions that transform raw advertising data into actionable business insights and leverage rich analytics data to create sophisticated sport audience segments.
THE CHALLENGE
We're scaling rapidly and need a senior data engineer who can take ownership of complex, multi-faceted data projects. You'll be tackling challenges like:
ABOUT YOU
OUR OFFER:
A collaborative environment with colleagues from all over the world (Engineering offices in Europe, Asia and US)
Ability to shape your own workday and career via a clearly defined professional and personal development plan
Opportunity to work with senior leadership, develop yourself and build your career within an inspiring and fast-growing company and digital sports environment.
A vibrant and inclusive community, including Women in Tech and Pride groups which welcome all participants
A company culture that promotes social aspects, sports, physical exercise and fun.
Innovative and cross-team challenges like ShipIt, office sports tournaments in Darts and Table Tennis and unique beer brewing competitions.
Competitive salary and benefits (e.g. retirement pension and insurance plan)
Sportradar takes over the full costs of € 365.- for the Öffi-Ticket (Jahreskarte) for you
OUR RECRUITMENT PROCESS:
Initial Screening: A quick chat with our Talent Acquisition Partner to understand your background and expectations.
Technical: Theoretical Interview: 60 minutes to discuss your technical skills on the theoretical level with the technical team.
Technical: Coding Interview: 60 minutes of live coding where we do not access the end result but rather the candidate's approach (clean code and thinking process).
System Design Interview: 60 minutes to solve a high-level problem with certain requirements.
Final Steps: Receive final feedback while onsite visit might be requested and, if successful, an offer!
We believe great products are built by great teams working closely together. While we offer flexible working hours, this role is fully office-based, as we strongly value in-person collaboration, knowledge sharing, fast decision-making, and team connection. We see working together onsite as a key driver of innovation, learning, and success. Certain exemptions may apply depending on location - your local point of contact can provide further details.
The minimum monthly salary for this position is according to the Collective Bargaining Agreement. Overpayment will be considered depending on qualifications and working experience.
At Sportradar, we celebrate our diverse group of hardworking employees. Sportradar is committed to ensuring equal access to its programs, facilities, and employment opportunities. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We encourage you to apply even if you only meet most of the requirements (but not 100% of the listed criteria) – we believe skills evolve over time. If you’re willing to learn and grow with us, we invite you to join our team!
- Processing and analyzing terabytes of advertising data with sub-second query performance - Building and maintaining robust ETL pipelines using Spark and AWS services - Designing and building scalable data processing systems - Developing backend APIs and microservices (Python or Go) - Architecting data flows that support both batch and real-time analytics requirements - Implementing robust monitoring and alerting systems to detect data quality issues - Managing AWS infrastructure using Terraform - Implementing CI/CD best practices and maintaining high coding standards - Leading large-scale data projects from requirements gathering through delivery - Mentoring team members - 5+ years of data engineering experience with proven track record of leading complex data projects - Exceptional communication skills and experience working in cross-functional teams - Very strong hands-on experience with AWS services (S3, Lambda, Glue, Athena, Redshift, EMR, etc.) - Proficiency with Apache Spark for large-scale data processing - Strong experience with Python for building data processing services and APIs - Expert-level SQL for data processing and analytics - Hands-on experience with Docker, Terraform, and CI/CD pipelines - Strong commitment to writing clean, maintainable, well-documented code with comprehensive testing - Experience designing scalable data architectures, data modeling, and optimizing data processing workflows - Experience creating and managing analytics dashboards in BI tools (Tableau, Qlik Sense, Quicksuite, Power BI)