<div><p>At Underdog, we make sports more fun.</p> <p>Our thesis is simple: build the best products and we’ll build the biggest company in the space, because there’s so much more to be built for sports fans. We’re just over five years in, and we’re one of the fastest-growing sports companies ever, most recently valued at $1.3B. And it’s still the early days.</p> <p>We’ve built and scaled multiple games and products across fantasy sports, sports betting, and prediction markets, all united in one seamless, simple, easy to use, intuitive and fun app. </p> <p>Underdog isn’t for everyone. One of our core values is give a sh*t. The people who win here are the ones who care, push, and perform. If that’s you, come join us.</p> <p>Winning as an Underdog is more fun.</p></div><p>This role offers the opportunity to redesign and scale the backbone of Underdog’s data and machine learning platform, directly shaping how data powers products and decisions across the company. You’ll not only drive technical excellence in areas like data quality, availability, and scalability, but also lead a high-\ performing team in building innovative data systems that support a rapidly growing business. By partnering across product, engineering, and analytics, you’ll have a unique chance to influence both the technology stack and the strategic impact of data at scale.</p> <h3>About the role</h3> <ul> <li>As an Engineering Manager - Data &amp; ML, you’ll be responsible for roadmapping and technically architecting a scalable data and machine learning platform</li> <li>Establish best practices that achieve operational excellence in data availability, data quality, and data observability</li> <li>Collaborate with the data science, data analytics, and product teams to deliver high-impact data assets in a fast paced environment</li> <li>Manage relevant cloud infrastructure for hosting big data applications and ML workloads such as SageMaker, Kubeflow, or Vertex AI</li> <li>Design and implement data pipelines that are optimized for scale and data quality</li> <li>Lead, mentor, and scale the data engineering team, cultivating a culture of innovation, learning, and excellence</li> <li>Partner with product, engineering, and analytics teams to understand their data needs and translate their business requirements to scalable technical solutions</li> <li>Stay on top of industry trends, emerging technologies, and best practices for data processing, storage, compute and ML development</li> <li>Develop and maintain robust governance frameworks, ensuring processes for monitoring, documentation, and testing are in place to safeguard the integrity and availability of data</li> </ul> <h3>Who you are</h3> <ul> <li>At least 8+ years of experience in data engineering, data infrastructure, and/or machine learning roles with experience architecting near real time big data systems</li> <li>2+ years of experience managing 5+ person teams</li> <li>Highly focused on delivering results for internal and external stakeholders in a fast-paced, entrepreneurial environment</li> <li>Strong familiarity with distributed computing and data storage mechanisms on the cloud environment (e.g. AWS/GCP/Azure) with hands-on experience in managing data infrastructure</li> <li>Track record of delivering scalable and innovative solutions, leveraging cutting-edge technologies for data and machine learning technologies such as Spark, Iceberg, Kafka, and SageMaker</li> <li>Demonstrates strong ownership and thrives in a fast paced environment, consistently driving initiatives forward and delivering results with urgency</li> <li>Excellent leadership and communication skills with ability to influence and collaborate with stakeholders</li> <li>Advanced degree in Computer Science, Data Science, or a related field</li> <li>Expert proficiency with Python and SQL</li> <li>Expert proficiency with Terraform or other Infrastructure as Code (IAC) tools</li> </ul> <h3>Even better if you have</h3> <ul> <li>Strong interest in sports and/or sports betting</li> <li>Experience building ML systems like recommendation engines</li> </ul> <p> </p> <p><em>Our target starting base salary range for this position is between $208,000 and $310,000, plus pre-IPO equity. Our comp range reflects the full scale of expected compensation for this role. Offers are calibrated based on experience, skills, impact, and geographies. Most new hires land in the lower half of the band, with the opportunity to advance toward the upper end over time.</em></p> <h3>What we can offer you:</h3> <ul> <li>Unlimited PTO (were extremely flexible with the exception of the first few weeks before &amp; into the NFL season)</li> <li>16 weeks of fully paid parental leave</li> <li>Home office stipend</li> <li>A connected virtual first culture with a highly engaged distributed workforce</li> <li>5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents</li> </ul> <p>#LI-REMOTE</p><div><h4><strong><em>This position may require sports betting licensure based on certain state regulations.</em></strong></h4> <p><em>Underdog is an equal opportunity employer and doesnt discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic.</em></p></div>

Underdog Fantasy

Engineering Manager - Data & ML

Underdog Fantasy