Engineering Manager, Data Distribution

**A bit about us**:
Do you want to join one of the world's fastest growing sports technology companies? Genius Sports is at the epicentre of the global network connecting sports, brands and fans through official live data. Our mission is simple. We champion a more sustainable sports data ecosystem that benefits all parties.

We're looking for enthusiastic and ambitious people to join our talented team.

If you see yourself becoming part of a global family building the future of sports entertainment together, then come and grow with us. We put trust in our people to deliver the difference for our clients around the world. It's why many of the world's largest leagues & federations such as the NFL, English Premier League, FIBA and NCAA choose to work with Genius Sports.

**The Role: Engineering Manager, Data Distribution**

The Genius Sports Data Engineering Team is looking for a smart, talented, and experienced Engineering Manager to lead a team of engineers responsible for modernizing our data distribution pipeline in support of our sports data, betting, broadcast, and fan engagement offerings.

Additionally, he or she will have a track record of building high-performing engineering teams and a passion for developing a team culture of innovation and quality to solve for unique complex problems.

This role is based in our office in Medellin, Colombia. Located in the country's tech hub Medellin, we have a team of 400 working in delivery and technology, computer vision, sportsbook trading, live data capture and client services.

**Responsibilities**:
Specific responsibilities for the Engineering Manager, Data Distribution and his/her team include the following:
**Build, Maintain, and Evolve our Data Distribution Pipeline**
- Partner with Sports Data Engineering and Product teams to understand and support requirements for evolving data pipeline for distributing internally and to external customers our real-time data streams that are powered by various data sources such as human and computer-vision driven tools for collecting live sports event data (e.g., passes, rushes, touchdowns, turnovers, etc.) at the team and individual player level
- Identify and analyze existing data distribution methods for delivering multiple data streams from various domains (e.g., fixtures data, odds data, player and match data). Collaborate closely with variety of stakeholders (Sports Betting, Fan Engagement, Advertising, leagues, etc.) to understand business needs and to evolve our data distribution architecture to meet the changing business needs
- Design, build, and maintain a robust, real-time big data pipeline for distributing terabytes of rich sports, betting, and media data streams via modern Pull and Push APIs, utilizing GraphQL and streaming technologies
- Build reliable end-to-end monitoring, alerting, and reporting capabilities to assist in maintaining highly functional, low latency, performant data distribution
- Lead the creation of the API technical strategy, reviewing with domain experts and business stakeholders to ensure we can support the evolving needs of our data consumers

**Leadership**
- Build, coach and lead a team of high-performing, passionate, platform and full-stack engineers, able to execute quickly without sacrificing quality
- Ensure timely, high quality delivery of agreed business value, balancing pragmatism with technical sustainability
- Bring an ownership mindset to the table. Enable a team-first culture, where teams feel secure to iterate, fail and learn rapidly with accountability
- Ensure the team has the right resources, skills and time, managing stakeholders effectively to ensure that we can build a high-quality data product to support the organization

**Position Requirements
**_Required Skills _**
- 6+ years of software engineering experience with heavy emphasis on data processing and distribution
- 3+ years of experience leading engineering teams and building great engineering cultures
- Strong understanding of JVM based programming language (Java, Kotlin) and the ability to effectively build production-ready code for higher-complexity tasks3
- Experience in designing, developing and managing GraphQL APIs with GraphQL Federation architecture and API layers for data consumptions and distribution
- Experience with data modelling and optimization of data structures based on consumption patterns
- Experience with Big Data and deep familiarity with high volume web services/APIs
- Expertise in real-time data streaming systems, ideally from a high transaction volume industry (e.g., financial/banking, online services, retail, etc.) using low-latency stream-processing technologies such as Kafka, Flink or Pulsar
- Experience with SQL and NoSQL databases. Excellent knowledge of performance tuning
- Experience with conceptualization, design and assistance in the implementation of new and existing systems, data processing, distribution and production architectures

**_Desirable Skills _**
- Familiarity o