DraftKings

Gaming

LeadDataPlatformEngineer

London, United Kingdom FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Data Platform Engineer at DraftKings. Skills: Databricks, AWS, Terraform, Python. Own and operate Databricks infrastructure. Build and manage cloud infrastructure”

What You'll Achieve.

Make model development, training, and deployment fast, repeatable, and cost-aware; Move from ideas to impact without friction; Strengthen reliability, automation, and developer experience; Improve platform efficiency, usability, and governance

Industry & Context.

Gaming
Eligibility Requirements

May be required to obtain a gaming license

What They're Looking For.

Must Have

At least 5 years of experience in machine learning platform, data platform, data engineering, or infrastructure engineering roles, Hands-on experience administering and operating Databricks in production environments, Deep familiarity with infrastructure as code, including Terraform or Pulumi, and proven ability to manage change safely at scale, Experience with AWS, Docker, Kubernetes, and continuous integration and continuous delivery pipelines, Python skills and familiarity with machine learning tooling such as MLflow, pandas, and scikit-learn, A track record of owning complex systems end to end, including reliability improvements, incident follow-up, and performance tuning, Clear, confident communication skills, including technical documentation and the ability to align cross-functional partners

What You'll Do.

Own and operate Databricks infrastructure

Build and manage cloud infrastructure

Author and review technical designs

Partner closely with data scientists

Drive engineering initiatives

Stay current on data platform trends

Coach and mentor teammates

How You'll Work.

Team & Collaboration

Partner closely with data scientists, data engineers, machine learning engineers, and Infrastructure teams; Align platform capabilities to real-world needs; Align cross-functional partners

Communication Scope

Clear, confident communication skills; Technical documentation

Process & Methodology

Lead projects end to end, Technical planning through delivery

Full Job Description

At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. ## The Crown Is Yours As a Lead Data Platform Engineer, you’ll design, build, and operate the machine learning platform and Databricks infrastructure that powers scalable, reliable data science at DraftKings. You’ll own the backbone that makes model development, training, and deployment fast, repeatable, and cost-aware-so teams can move from ideas to impact without friction. Working alongside Data Science, Machine Learning, Data Engineering, and Infrastructure partners, you’ll turn evolving use cases into durable platform capabilities. You’ll lead projects end to end, strengthening reliability, automation, and developer experience across the stack. ## ****What you’ll do as a Lead Data Platform Engineer**** * Own and operate Databricks infrastructure with a focus on reliability, scalability, performance, and cost optimization. * Build and manage cloud infrastructure on Amazon Web Services using infrastructure-as-code tools like Terraform. * Author and review technical designs that enable scalable, automated, and reproducible machine learning workflows. * Partner closely with data scientists, data engineers, machine learning engineers, and Infrastructure teams to align platform capabilities to real-world needs. * Drive engineering initiatives from technical planning through delivery, production rollout, and long-term maintenance. * Stay current on data platform and machine learning platform trends, applying best practices that improve platform efficiency, usabi

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