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# Staff Data Platform Engineer

- **Company:** Prizepicks Llc
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $200,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Big Data, BigQuery, Databases, Continuous Integration, Information Engineering, Data Infrastructure, Data Security, Distributed Computing Environment, Elasticsearch, Fault Tolerance, High-Frequency Trading, Information Lifecycle Management, Python (Programming Language), Machine Learning, Package Management Systems, Redis, Cloud Services, Data Streaming, Data Storage Technologies, Apache Spark, Build Management, Containerization, Data Lakes, Core Data, Kubernetes, Data Lineage, Apache Flink, Real Time Data, Apache Kafka, Data Management, Presto, Restful APIs, Data Pipelines, Docker
- **Published:** September 17, 2026
- **Apply:** http://prizepicks.com/position?source=TeamWork&utm_source=TeamWork&gh_src=6d1fddd73us&gh_jid=7992819003

## About the Role

* 8+ 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 <100ms.
 * Proficient with Containerization, Docker, Kubernetes and cluster level management.
 * Extensive experience in Big data technologies like Spark, Flink, Kafka or Kinesis, Argo/Airflow, Polaris, OpenMetadata, Iceberg, Lakehouse, Redis, Elasticsearch, Databases. Experience with building REST APIs, package management and have built libraries.
 * 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.
 * Should have been a key contributor to projects through the entire development lifecycle from concept to release., You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

## Description

As a Staff Data Platform Engineer, you will contribute to architecting and 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., * 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 architecting an end to end data platform, making improvements for automation & scaling, and enforcing 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%
 * Cross-Functional Collaboration: Partner with Product, Backend Engineering, Data Engineering and Data Science teams to operationalize complex Data engineering and Data science capabilities-balancing platform stability, architectural standards, and rapid iteration., * Experience implementing data platform infrastructure while enforcing best practices for deployment of a large scale data platform.
 * Designed and built scalable, fault-tolerant data storage, distributed processing systems, and data lakes at massive scale, worked with technologies - Apache Spark, Flink, Trino, Presto, or Kafka.
 * Built internal tools for data pipeline authoring, orchestration, and AI-assisted analytics to boost developer productivity.
 * Established policies and tooling for data quality, compliance, lineage, and secure access control.
 * Enabled self-service for Data teams for pipeline development and deployment.
 * Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading or similar domain expertise.