Senior Data Engineer

Sportradar Austria
Wien, Austria
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Clean Code Principles Query Performance Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Big Data Continuous Delivery Continuous Integration Data Architecture Information Engineering Extract Transform Load (ETL)
+22 more
Data Systems Data Visualization Python (Programming Language) Power BI SQL Databases Data Streaming System Testing Tableau (Software) Qliksense Data Processing GitHub Copilot System Availability Prompt Engineering Apache Spark Generative AI Backend Claude Terraform Data Pipelines Docker Web Api Microservices

Job description

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, 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.

Requirements

  • 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
  • AWS & Data Engineering: 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
  • Backend Development: Strong experience with Python for building data processing services and APIs, plus expert-level SQL for data processing and analytics
  • Infrastructure & DevOps: Hands-on experience with Docker, Terraform, and CI/CD pipelines with automation best practices for data systems
  • Clean Code Advocate: Strong commitment to writing clean, maintainable, well-documented code with comprehensive testing and deep knowledge of analytics/reporting requirements
  • Data Architecture: Experience designing scalable data architectures, data modeling, and optimizing data processing workflows
  • Dashboard Development: 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

About the company

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., 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.

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