Senior Software Engineer - Data (Python, AWS)
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.
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:
Scale & Performance Engineering : Processing and analyzing terabytes of advertising data with sub-second query performance while building and maintaining robust ETL pipelines using Spark and AWS services to handle massive data volumes daily
Data Pipeline Architecture & Development : 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, and managing user-facing dashboards that visualize complex data insights
Infrastructure & Data Quality Operations : 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 across data processing systems
Cross-Functional Leadership & Collaboration : Leading large-scale data projects from requirements gathering through delivery, bridging technical implementation with business requirements, mentoring team members, and presenting technical concepts to stakeholders while challenging requirements constructively
End-to-End Data System Ownership : Taking complete ownership of complex data engineering projects while ensuring high availability and accuracy for both internal stakeholders and external clients, championing clean code principles, and serving as a knowledge leader who supports delivering the right data solutions
- Processing and analyzing terabytes of advertising data with sub-second query performance while building and maintaining robust ETL pipelines using Spark and AWS services to handle massive data volumes daily
- 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, and managing user-facing dashboards that visualize complex data insights
- 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 across data processing systems
- Leading large-scale data projects from requirements gathering through delivery, bridging technical implementation with business requirements, mentoring team members, and presenting technical concepts to stakeholders while challenging requirements constructively
- Taking complete ownership of complex data engineering projects while ensuring high availability and accuracy for both internal stakeholders and external clients, championing clean code principles, and serving as a knowledge leader who supports delivering the right data solutions
- 5+ 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.) and proficiency with Apache Spark for large-scale data processing
- Strong experience with Python for building data processing services and APIs, plus 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 and 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) and data visualization solutions to present complex insights to stakeholders
- GenAI Tools (beneficial): Experience working with contextual and prompt engineering with GitHub Copilot, Claude, or similar AI assistants
- 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