Data Platform Engineer
$145,000–$175,000 year
On-siteAtlanta, Georgia, United States
Job Summary
Design and build the Data platform for Batch and Streaming use cases, integrating low-latency ML models to support dynamic oddsmaking, risk analysis, and smart deposit defaults. Build and maintain a platform with cutting-edge technologies, including data catalog and lineage capabilities, while enforcing robust security architectures. Champion best practices for model deployment, monitoring, and CI/CD to ensure 99.99% availability across the ecosystem. This role requires 3+ years of Platform Engineering experience with proficiency in streaming architectures, containerization, and Python/Go. Salary range is $145,000 to $175,000. We are looking for candidates based in Atlanta or 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 implementing infrastructure while enforcing best practices for deployment of a large scale data platform
- Experience building and scaling data platforms that successfully bridge batch historical data with real-time event streams
- Enabling self-service for Data teams for pipeline development and deployment
- 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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