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Sportradar's Ads Analytics team is the backbone of their advertising intelligence platform, processing terabytes of data daily from programmatic, social, and search advertising channels. The team builds end-to-end solutions that transform raw advertising data into actionable business insights and creates sophisticated sport audience segments.
As a Senior Data Engineer, you will take ownership of complex, multi-faceted data projects and tackle challenges across multiple dimensions:
**Scale & Performance Engineering**: Process and analyze terabytes of advertising data with sub-second query performance. Build and maintain robust ETL pipelines using Spark and AWS services to handle massive data volumes daily.
**Data Pipeline Architecture & Development**: Design and build scalable data processing systems. Develop backend APIs and microservices in Python or Go. Architect data flows that support both batch and real-time analytics requirements. Manage user-facing dashboards that visualize complex data insights.
**Infrastructure & Data Quality Operations**: Implement robust monitoring and alerting systems to detect data quality issues. Manage AWS infrastructure using Terraform. Implement CI/CD best practices and maintain high coding standards across data processing systems.
**Cross-Functional Leadership & Collaboration**: Lead large-scale data projects from requirements gathering through delivery. Bridge technical implementation with business requirements. Mentor team members and present technical concepts to stakeholders while challenging requirements constructively.
**End-to-End Data System Ownership**: Take complete ownership of complex data engineering projects while ensuring high availability and accuracy for both internal stakeholders and external clients. Champion clean code principles and serve as a knowledge leader supporting delivery of the right data solutions.
Sportradar is the world's leading sports technology company at the intersection of sports, media, and betting. More than 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries rely on their technology. The company offers a collaborative environment with engineering offices in Europe, Asia, and the US, professional development opportunities, and a vibrant inclusive community.
**Requirements:**
- 3+ years of data engineering experience with proven track record of leading complex data projects from conception to delivery
- Exceptional communication skills and experience working in cross-functional teams with analysts, product managers, and business stakeholders
- 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 with automation best practices for data systems
- Strong commitment to writing clean, maintainable, well-documented code with comprehensive testing
- Deep knowledge of analytics/reporting requirements
- 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)
- Beneficial: Experience with GenAI tools and contextual/prompt engineering (GitHub Copilot, Claude, or similar)
