Data Platform Engineer
$145,000–$175,000 year
RemoteAtlanta, Georgia, United States
Job Summary
Design and build scalable batch and streaming data platforms integrating low-latency ML models for dynamic oddsmaking and risk analysis. Deploy real-time services to pipe data for near real-time use cases, powering decisions across the sports betting and daily fantasy ecosystems. Champion best practices for model deployment, monitoring, and CI/CD to ensure 99.99% platform availability and complete observability. This role requires 3+ years of experience in Platform Engineering with proficiency in Python, Go, and streaming architectures like Kafka and Flink. We are the fastest-growing sports company in North America, recognized by Inc. 5000, and are open to qualified applicants from anywhere in the U.S.
Required Qualifications
- 3+ years of experience in Platform Engineering
- Proven track record of deploying and maintaining scalable Data platforms in high-traffic production environments
- Proficiency in streaming architectures (Kafka/Flink/PubSub)
- Ability to build low-latency services to serve stream ingestion and processing
- Proficiency with Containerization, Docker, Kubernetes and cluster-level management
- Expertise in coding with Python and Go
- Deep experience with Cloud services
- Experience with Big data technologies like Spark, Flink, Kafka or Kinesis, Argo/Airflow, Polaris, OpenMetadata, Iceberg, Lakehouse, Redis, Elasticsearch, and Databases
- Experience building REST APIs, package management and libraries
- Key contributor to projects through the entire development lifecycle from concept to release
- Must be authorized to work for any employer in the U.S.
- Must be available for remote work or be based in Atlanta, U.S.
Desired Qualifications
- Preferred experience with GCP services (BigQuery, Cloud Functions, GKE) or AWS equivalents
- Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading
- Experience building and scaling data platforms that successfully bridge batch historical data with real-time event streams
- Experience enabling self-service for Data teams for pipeline development and deployment
- Experience enabling AI agents for repetitive tasks and AI coding for faster and iterative software development
- Excellent communication skills
- Stakeholder management
- Outstanding problem-solving skills
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