Staff 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 will lead the technical design and implementation of critical data infrastructure and products. You will design scalable batch and streaming pipelines, establish data architecture and engineering standards, translate business requirements into data solutions, lead technical reviews, improve data quality and reliability, and guide other data engineers.
Requirements
- 8+ years of experience in data engineering or a related field
- Data systems and platforms supporting ML, Analytics, and AI use cases
- Spark
- Airflow
- Kafka
- Databricks
- AWS, GCP, or Azure
- Data modeling
- Distributed systems
- ETL/ELT pipelines
- Streaming architectures
- SQL
- Python, Scala, or Java
- End-to-end technical system ownership
- Data governance
- Privacy
- Compliance
- Infrastructure as code
- Terraform
- Data platform observability
Responsibilities
- Design and implement scalable batch and streaming data pipelines
- Define standards for data modeling, data product design, and pipeline orchestration
- Translate business and analytical requirements into end-to-end data solutions
- Establish engineering practices for code quality, testing, documentation, and deployment
- Contribute to the evolution of the data platform
- Lead technical design and code reviews
- Mentor peers
- Partner with data platform, analytics, and data science teams
- Identify and resolve architectural bottlenecks
- Drive improvements in data quality, lineage, observability, and reliability
- Act as a technical liaison across engineering, product, and analytics teams
- Provide technical leadership to data engineers
- Evaluate and onboard new technologies and frameworks
Benefits
- Health insurance
- Vision insurance
- Dental insurance
- Life insurance
- Disability insurance
- 401(k) matching up to 5%
- Paid time off
- Sick leave
- Annual bonus
- Long-term incentives
- Commuter benefits
- Pet insurance
- Paid company holidays