Senior Data Infrastructure Engineer
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Job description
As Senior Data Infrastructure Engineer at Fanalysis, you'll own and evolve the AWS data infrastructure that powers our real-time sports analytics. You'll own the serverless architecture that intelligently polls live match data, moves data between services, and supports delivering insights to broadcast partners within strict SLA requirements. Your work will be critical as we scale from hundreds to millions of users, maintain sub-10 minute data delivery to Sky Sports, expand our data product offering, and onboard international broadcast partners., * You'll own our AWS data infra. Currently, this is lambda pipelines in and out of S3, orchestrated with step functions, and deployed in CDK
- You'll own and evolve our orchestration strategy, which adapts frequency based on match schedules. You'll own the pipelines that handle Opta Sports API, backend sync, and warehouse integration
- Ultimately, you'll design and build infrastructure solutions for scaling the processing of millions of users' data at sub-5 minute latency. As our roadmap develops, this will mean streaming solutions for real-time analytics at scale, or large-scale processing of text data from user reviews and community discussions
- You'll be essential for ensuring our 99.9%+ uptime for broadcast partner data delivery, within sub-10 minute SLAs
- You'll build comprehensive monitoring, alerting, and observability systems across all data pipelines
- You'll manage multi-environment deployments with CI/CD
- You'll set our standards: Infrastructure as Code using AWS CDK, automated deployment processes, and wide test coverage
- You'll collaborate on data architecture decisions and technical roadmap planning
- You'll contribute to data governance, security, and compliance frameworks for international expansion
Requirements
We know that great talent comes in many forms; if you're excited about this role but don't tick every single box, we'd still love to hear from you.
- 5+ years of AWS infrastructure experience in data-heavy, high-scale environments, including serverless architectures
- Strong background in real-time data processing or high-frequency batch pipelines
- Strong background in DevOps practices, CI/CD pipelines, and automated testing
- Experience scaling infrastructure 10x+ in startup or high-growth environments
- Experience with data pipeline orchestration, ETL/ELT processes, and data integration patterns
- Experience with streaming technologies (Kafka, Kinesis) and/or distributed processing frameworks (Apache Spark, AWS EMR)
- Experience with monitoring and observability tools, alerting systems, and SLA management
- Deep understanding of our current AWS services: Lambda, Step Functions, S3, IAM, CloudWatch
- Proficiency in Infrastructure as Code (AWS CDK)
- Knowledge of database systems (MongoDB is a plus) and data warehouses
- Knowledge of security best practices, IAM policies, and data governance
- Strong problem-solving skills and attention to detail for mission-critical systems
- Collaborative mindset for working with data scientists and engineers
- Comfort with startup pace and ability to balance technical excellence with rapid delivery
- Sports data, real-time analytics, or data-as-a-product background is a plus
- Understanding of data compliance requirements and international data regulations is a plus
This is a full-time role based in London. Our office is in Soho and we believe in the benefits of working together, so ideally you'd be able to join us in the office at least 3 days a week.
