Senior Analytics Engineer

Posted Yesterday
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New York, NY, USA
Hybrid
165K-180K Annually
Senior level
AdTech • Artificial Intelligence • Machine Learning • Marketing Tech • Software • Sports • Big Data Analytics
Welcome to the intelligent sports era.
The Role
The Senior Analytics Engineer will build and maintain data models, ensure consistent KPIs, and drive self-service analytics, partnering with multiple business teams to enhance data usage.
Summary Generated by Built In


By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalised than ever before. Learn more at geniussports.com   


The Role - Senior Analytics Engineer
 

We are hiring a Senior Analytics Engineer on our Enterprise Technology team to own and scale the semantic and presentation layers of our data platform. 

This is a hands-on individual contributor role focused on building high-quality, scalable data models and defining standardized metrics across the business. You will sit at the intersection of data analytics and business stakeholders, ensuring our data is structured for both performance and usability. 

You will directly influence how data is consumed across Product, Commercial, Finance, and Operations, enabling consistent, self-service analytics at scale. This role is expected to elevate data from a reporting function to a core business enabler and revenue driver. You will design data models, metrics, and analytics capabilities that directly influence commercial outcomes, product performance, and operational efficiency. 


What You Will Do
 

Own the Semantic & Presentation Layer 

  • Design and maintain core data models and metrics used across the business 
  • Establish a single, standardized layer of business logic for reporting and analytics 
  • Ensure consistency in KPI definitions across teams 

Build Scalable Data Models 

  • Develop and optimize models in dbt (or equivalent) on top of Snowflake 
  • Structure data for performance, reusability, and clarity 
  • Partner across the business to improve pipeline efficiency and reliability 

Drive Self-Service Analytics 

  • Create intuitive, well-documented datasets that reduce reliance on analysts 
  • Improve adoption of BI tools (Sigma, or similar) 
  • Enable business users to explore data confidently without duplication of logic 

Define the BI & Metrics Strategy 

  • Standardize metric definitions and governance across domains 
  • Contribute to data modeling best practices and design standards 
  • Support the evolution toward AI-enabled analytics and semantic layer exposure 

Drive Business Impact Through Data 

  • Partner with Product, Commercial, and Finance teams to define metrics that directly influence revenue, margin, and customer outcomes 
  • Translate business strategy into measurable data models and KPIs that inform pricing, performance, and growth decisions 
  • Identify opportunities where improved data modeling and analytics can unlock new revenue streams or optimize existing ones 
  • Ensure analytics outputs are actionable, not just descriptive, with clear linkage to business decisions 

Mentorship & Influence 

  • Drive best practices in SQL, modeling, and BI design 
  • Partner with stakeholders to align on definitions, priorities, and data strategy 

 

Qualifications 

Experience 

  • 6+ years in analytics engineering, BI engineering, or data engineering 
  • Experience working in a modern cloud data stack (Snowflake preferred) 

Technical Skills 

  • Demonstrable experience of, and technical proficiency in, some or most of DBT Cloud, Databricks, Snowflake, Gitlab, Fivetran. 
  • Strong experience with BI tools (Sigma etc.) 
  • Deep understanding of: 
  • Dimensional modeling 
  • Semantic layer design 
  • Data warehousing best practices (Snowflake)  
  • Demonstrable experience extracting data from APIs to surface to raw layers in data warehouses 

Data & Product Thinking 

  • Ability to translate business questions into clean, reusable data models 
  • Experience defining and governing business-critical metrics 
  • Focus on performance, usability, and long-term scalability 

Execution & Influence 

  • Strong stakeholder management across technical and business teams 
  • Proven ability to drive adoption of self-service analytics 
  • Ownership mindset with a bias toward simplification and standardization 

What Success Looks Like 

  • A trusted, centralized semantic layer used across the company 
  • Clear, consistent KPI definitions with no duplication or conflict 
  • Increased self-service adoption across business teams 
  • Reduced time to insight for Product, Commercial, and Operations 
  • Scalable foundation for AI-driven analytics and reporting 
  • Data is consistently used to drive revenue growth, margin improvement, and product performance decisions 
  • Business stakeholders rely on the data platform to make decisions, not just monitor results 
  • Analytics outputs are directly tied to commercial outcomes and measurable business impact 

 

What’s in it for you?  
 
The salary for this role is based on an annualized salary range of $165,000 – 180,000. 
This role will also be eligible to take part in Genius Sports Group's benefits plan.    
 
Our benefits include health insurance, skills training and much more, depending on the location. We also offer a host of softer benefits, including many social events throughout the year such as summer and winter holiday parties, monthly team building events, sports tournaments, charity days and wellbeing activities. For more details on the compensation and benefits package, please get in touch with our Talent team.   
  

How we work  
 
We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together. This role is based in NYC and is required to work from our office 4 days a week.  
 
As well as a competitive salary and range of benefits, we’re committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports.   
 
One team, being brave, driving change   
 
We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Diversity | Genius  
 
Let us know when you apply if you need any assistance during the recruiting process due to a disability. 

What the Team is Saying

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The Company
HQ: New York, NY
1,800 Employees
Year Founded: 2001

What We Do

Genius Sports is the layer between what happens on the field and how the world engages with it. Our solutions across the global sports ecosystem are underpinned by our next generation big data and artificial intelligence platform, GeniusIQ. By ingesting and computing multiple real-time data feeds, GeniusIQ powers a wide range of functions and applications across sports performance and officiation, fan engagement, advertising, and sports betting. Founded in 2001, Genius Sports is now one of the world’s largest sports technology companies, working with the likes of the NFL, NBA, EPL, FIBA, ESPN, Sky Sports, Flutter, DraftKings and 100s more. We're headquartered in New York and London, with offices in Los Angeles, Medellin, Tallinn, Sofia, Singapore, Lausanne, Manchester and Melbourne.

Why Work With Us

We are one team, being brave, driving change. Our company values help create a cohesive culture, where we think, feel and act like One Genius. We strive to create an environment where everyone feels a sense of belonging and the ability to make a difference, driving our vision to be everywhere in sports, redefining experiences through technology.

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Genius Sports Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Not Specified
HQNew York, NY
Bologna, IT
Lausanne, CH
London, GB
Los Angeles, CA
Manchester, GB
Medellín, CO
Melbourne, VIC
Salerno, IT
Singapore
Sofia, BG
Vilniaus miesto, LT
Zaporizhzhia, UA
Learn more

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