Job Description
The Opportunity:
Are you ready to power one of the world's most significant sporting events? Global Sports Analytics is seeking a visionary Senior Data Engineer to join our elite project team dedicated to the 2026 FIFA World Cup infrastructure. You will be at the forefront of building scalable, high-performance data ecosystems that process millions of events in real-time.
The Role:
In this pivotal role, you will design and implement robust data pipelines and architectures that support complex analytics, fan engagement tools, and operational logistics. If you thrive in fast-paced environments and want to leave a lasting legacy in sports technology, this is your chance to make history.
Why Join Us?
* Impact: Directly contribute to the digital backbone of the 2026 World Cup.
* Innovation: Work with cutting-edge Big Data technologies and AI-driven insights.
* Growth: Accelerate your career with exposure to enterprise-scale data challenges.
Responsibilities
- Architect Scalable Solutions: Design and implement distributed data architectures capable of handling high-throughput, low-latency data ingestion for millions of concurrent users.
- ETL Pipeline Development: Build and maintain complex ETL/ELT pipelines using Python, Spark, and cloud-native services to transform raw data into actionable insights.
- Real-Time Analytics: Develop real-time streaming data pipelines (Kafka, Flink) to support live score updates and fan engagement dashboards.
- Data Governance & Security: Enforce strict data governance policies, ensuring compliance with GDPR and CCPA standards while securing sensitive fan and operational data.
- Collaborative Engineering: Partner with data scientists and product managers to translate business requirements into technical specifications and data models.
- Performance Optimization: Continuously monitor, tune, and optimize database performance to ensure 99.99% availability during peak events.
- Documentation: Create comprehensive technical documentation, data lineage diagrams, and API specifications for the engineering team.
Qualifications
- Education: Bachelor’s degree in Computer Science, Data Engineering, or a related technical field (Master’s degree preferred).
- Experience: 5+ years of professional experience as a Data Engineer or Software Engineer specializing in Big Data.
- Programming: Proficiency in Python and SQL with strong knowledge of object-oriented programming principles.
- Big Data Stack: Extensive experience with distributed processing frameworks like Apache Spark, Hadoop, or MapReduce.
- Cloud Platforms: Deep expertise in cloud providers (AWS, GCP, or Azure) and managed services (Redshift, BigQuery, Snowflake).
- Message Queues: Hands-on experience with message brokers such as Kafka or RabbitMQ.
- Soft Skills: Excellent problem-solving skills, strong communication abilities, and a proactive attitude in a collaborative environment.