As a Data Platform Engineer, you will contribute to building the modern Data platform at Prizepicks to scale and productionize our core data engineering, data analytics and machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.

What you’ll do:

• Build Scalable Data Platform: Design and build the Data platform for Batch and Streaming use cases. You will build and maintain a platform with cutting-edge technologies and enable data users by building data catalog and data lineage capabilities. You will be contributing to design and enforce robust data security architectures and controls.
• Real-Time data platform at Scale: Build platform for deploying low-latency services to pipe data for streaming or near real time use cases. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Data Platform Ops: You will champion best practices for model deployment, monitoring, and CI/CD for Data pipeline deployment. You will enable complete observability for batch and streaming data platform and ensure the availability of 99.99%

What you have:

• 3+ years of experience in Platform Engineering, with a proven track record of deploying and maintaining scalable Data platforms in high-traffic production environments.
• Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve stream ingestion and processing, which will serve model inference in
• Proficient with Containerization, Docker, Kubernetes and cluster-level management.
• Deep experience building a platform for managing the full Data lifecycle, including setting up a data exploration environment.
• Expert in coding with Python and Go. Deep experience with Cloud services, preferred with GCP services (BigQuery, Cloud Functions, GKE) or AWS equivalents.
• Excellent communication skills, stakeholder management and outstanding problem-solving skills.
• Extensive experience in Big data technologies like Spark, Flink, Kafka or Kinesis, Argo/Airflow, Polaris, OpenMetadata, Iceberg, Lakehouse, Redis, Elasticsearch, and Databases. Experience with building REST APIs, package management and have built libraries.
• Should have been a key contributor to projects through the entire development lifecycle from concept to release.

What makes you stand out:

• Experience implementing infrastructure while enforcing best practices for deployment of a large scale data platform.
• 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.
• 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.

Where you’ll live:

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