Senior Data Engineer
FanDuel is a premier US-based gaming destination, offering daily fantasy sports, sports betting, and online casino games. Founded in 2009 to innovate the fantasy sports industry, it has become a leading mobile sports betting operator, allowing users to bet on sports, play online games, and build fantasy teams across a wide array of professional sports leagues.
Funding history
Projects
About FanDuel
FanDuel is the premier gaming destination and #1 Sportsbook in the United States. What started as a backyard brainstorm in Texas in 2009 has grown into a major force in the gaming industry. The company revolutionized fantasy sports by simplifying the season-long game into daily contests, allowing fans to compete and win daily. Today, with over 12 million registered users, FanDuel offers a wide range of products including sports betting on leagues like the NFL, NBA, MLB, and NHL; an online casino with blackjack, slots, and live dealer games; daily fantasy sports for various sports like football, baseball, and basketball; and horse racing betting for major events. Additionally, FanDuel provides content through FanDuel TV and insights via FanDuel Research, making every moment of the game more engaging for its users.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You design and build scalable data solutions that support analytics, machine learning, and business operations. You develop reliable batch and streaming pipelines, create reusable data models, ensure data quality, follow engineering best practices, contribute to architecture discussions, collaborate with data teams, communicate technical risks, and mentor junior engineers.
Requirements
- 5+ years of data engineering or software engineering experience
- Strong SQL skills
- Fluency in Python, Scala, or Java
- Experience with Airflow, Spark, dbt, Kafka, or Databricks
- Understanding of data modeling and data warehousing
- Knowledge of data quality and observability
- Experience with AWS, GCP, or Azure
- Experience supporting analytics and machine learning workflows
- Familiarity with data governance, privacy, and compliance frameworks
- Familiarity with infrastructure-as-code or DevOps practices
Responsibilities
- Design and maintain scalable ETL and ELT pipelines
- Work with large-scale datasets
- Develop batch and streaming data pipelines
- Build data platforms using modern tools
- Create reusable data models and assets
- Translate business needs into production-ready data solutions
- Validate and monitor data quality
- Follow software engineering best practices
- Participate in technical design and architecture reviews
- Improve data platform performance and scalability
- Partner with data scientists, analysts, and product managers
- Communicate technical concepts, project status, and risks
- Mentor junior engineers
Benefits
- Health insurance
- Fertility and family planning programs
- Mental health support
- Fitness benefits
- Paid time off
- Paid sick leave
- Annual bonus
- Long-term incentive opportunities
- 401(k) with up to 5% match
- Commuter benefits
- Pet insurance
- Medical insurance
- Vision insurance
- Dental insurance
- Life insurance
- Disability insurance
- 14 paid company holidays
