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Engineering Manager - Data & ML

Engineering Manager - Data & ML

Underdog FantasyWashington, DC, US
15 days ago
Job type
  • Full-time
Job description

Engineering Manager - Data & ML

The fastest-growing sports gaming company, ever. We're here to make sports more fun. We pair intuitive user experiences with innovative game designs to build the best experience for sports fans in America.

Since 2020, we've launched four of today's most widely played fantasy games, and built the Underdog Sportsbook entirely in-house with our own tech. We move fast, act with urgency, and create experiences you won't find anywhere else.

With a $1.3 billion valuation and backing from investors like Spark Capital, SV Angel, Mark Cuban, Kevin Durant, Adam Schefter, and more, we're just getting started.

At Underdog, we play and win as a team. We take chances and are unafraid to attack hard problems. We face challenges with ambition and optimism. We play for the love of the game.

We're Underdog. And winning as an Underdog is just more fun.

Join us.

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.

About the Role

  • As an Engineering Manager - Data & ML, you'll be responsible for roadmapping and technically architecting a scalable data and machine learning platform.
  • Establish best practices that achieve operational excellence in data availability, data quality, and data observability.
  • Collaborate with the data science, data analytics, and product teams to deliver high-impact data assets in a fast paced environment.
  • Manage relevant cloud infrastructure for hosting big data applications and ML workloads such as SageMaker, Kubeflow, or Vertex AI.
  • Design and implement data pipelines that are optimized for scale and data quality.
  • Lead, mentor, and scale the data engineering team, cultivating a culture of innovation, learning, and excellence.
  • Partner with product, engineering, and analytics teams to understand their data needs and translate their business requirements to scalable technical solutions.
  • Stay on top of industry trends, emerging technologies, and best practices for data processing, storage, compute and ML development.
  • Develop and maintain robust governance frameworks, ensuring processes for monitoring, documentation, and testing are in place to safeguard the integrity and availability of data.

Who You Are

  • 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.
  • 2+ years of experience managing 5+ person teams.
  • Highly focused on delivering results for internal and external stakeholders in a fast-paced, entrepreneurial environment.
  • 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.
  • 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.
  • Demonstrates strong ownership and thrives in a fast-paced environment, consistently driving initiatives forward and delivering results with urgency.
  • Excellent leadership and communication skills with ability to influence and collaborate with stakeholders.
  • Advanced degree in Computer Science, Data Science, or a related field.
  • Expert proficiency with Python and SQL.
  • Expert proficiency with Terraform or other Infrastructure as Code (IAC) tools.
  • Even Better If You Have

  • Strong interest in sports and / or sports betting.
  • Experience building ML systems like recommendation engines.
  • Our target starting base salary range for this position is between $190,000 and $220,000, plus target equity. The starting base salary will depend on a number of factors including the candidate's skills and experience, among other things.

    What We Can Offer You :

  • Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
  • 16 weeks of fully paid parental leave
  • A $500 home office allowance
  • A connected virtual first culture with a highly engaged distributed workforce
  • 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents
  • This position may require sports betting licensure based on certain state regulations.

    Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic.

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