Senior Data Platform Engineer Databricks & AWS ML Pipelines

DraftKings; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

DraftKings is seeking a Senior Data Platform Engineer to build and operate the backbone of our ML infrastructure. You will own Databricks, design cloud infrastructure on AWS, and enable reproducible ML workflows. You’ll work closely with Data Science, ML Engineering, and Infra teams to deliver scalable, reliable platforms.

You’ll lead complex projects, document architecture, and mentor teammates while continually improving usability and efficiency of our data platform in a fast-paced environment.

Qualifications

• 3+ years in ML platform, data platform, infrastructure, or data engineering roles.
• Hands-on Databricks in production environment.
• Infra-as-code using Terraform or Pulumi.
• Proficiency with AWS and container technologies (Docker/Kubernetes).
• Strong Python skills with ML libraries (MLflow, pandas, scikit-learn).
• Experience owning and operating complex systems at scale.
• Clear, technical documentation and cross-functional collaboration.

Responsibilities

• Own and operate Databricks infrastructure for performance, reliability, and cost-efficiency.
• Build and manage cloud infrastructure using AWS and IaC tools like Terraform.
• Architect and document scalable systems for reproducible ML workflows.
• Collaborate with Data Scientists, Data Engineers, ML Engineers, and Infra partners.

Skills

ML platform experience

Data platform experience

Infrastructure engineering

Cloud infrastructure design

Python programming

Technical documentation

Tools

Databricks

Terraform

Pulumi

AWS

Docker

Kubernetes

Job description

DraftKings is seeking a Senior Data Platform Engineer to build and operate the backbone of our ML infrastructure. You will own Databricks, design cloud infrastructure on AWS, and enable reproducible ML workflows. You’ll work closely with Data Science, ML Engineering, and Infra teams to deliver scalable, reliable platforms.

You’ll lead complex projects, document architecture, and mentor teammates while continually improving usability and efficiency of our data platform in a fast-paced environment.