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PrizePicks

engineering opportunity

Data Platform Engineer

You will design and build a scalable data platform to support batch and streaming use cases while enabling data users with catalog and lineage capabilities. Additionally, you will champion best practices for model deployment, monitoring, and CI/CD to ensure high availability and observability of the data ecosystem.

Atlanta, Georgia, United StatesremoteFULL_TIME

Posted

About the role

What will you do at PrizePicks?

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike.

Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?

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 <100ms.

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:

While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote

Working at PrizePicks:

The typical salary range for this position is $145,000 to $175,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position.

Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process.

This application period will remain open for 30 days. We’re committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.

Date Posted: 8/3/2026

Benefits

you’ll receive:

In addition to your great compensation package, full-time employees will be eligible for the following perks:

Company-subsidized medical, dental, & vision plans

401(k) plan with company match

Annual bonus

Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)

Generous paid leave programs, including 16-week paid parental leave and disability benefits

Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked

Company-wide in-person events and team outings

Lifestyle enhancement program

Company equipment provided (Windows & Mac options)

Annual performance reviews with opportunities for growth and career development

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.

PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Which skills does this role require?

Platform EngineeringPythonGoKubernetesDockerData EngineeringMachine LearningCI/CDData ArchitectureStreaming ArchitecturesObservabilityData Platform EngineerPubSubStreamingBatch Processing

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