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
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
About the Role
You will design, build, and maintain scalable batch and streaming data pipelines that support analytics and business operations. You will write clean, efficient, well-documented code using Python, SQL, and Spark, and lead projects to build or improve data products. You will collaborate with data analysts, data scientists, and product managers to turn ambiguous business questions into actionable data solutions, participate in code reviews and agile ceremonies, monitor and troubleshoot pipelines, implement data quality checks, and document data sources, transformations, and architecture decisions.
Requirements
- 3+ years of experience in data engineering, analytics engineering, or software engineering with a focus on data
- Strong SQL skills and familiarity with at least one programming language (e.g., Python, Java, or Scala)
- Hands-on experience with modern data tools such as Databricks, Airflow, dbt, Spark, or Kafka
- Understanding of data modeling concepts, data warehousing, and ETL/ELT best practices
- Experience working with cloud-based data platforms (AWS, GCP, or Azure)
Responsibilities
- Design, build, and maintain scalable batch and streaming data pipelines
- Write clean, efficient, and well-documented code using Python, SQL, and Spark
- Ensure data reliability, accuracy, and timely delivery
- Lead projects to build or improve well-scoped data products
- Collaborate with data analysts, data scientists, and product managers to deliver actionable data solutions
- Translate business questions into engineering tasks and contribute to technical planning
- Participate in code reviews, sprint planning, and retrospectives
- Monitor data pipelines and troubleshoot issues
- Implement data quality checks and contribute to observability and testing practices
- Document data sources, transformations, and architecture decisions
Benefits
- Health plans including fertility and family planning programs, mental health support, and fitness benefits
- Generous paid time off (PTO & sick leave)
- Annual bonus and long-term incentive opportunities
- 401k with up to a 5% match
- Commuter benefits
- Pet insurance
- Medical, vision, and dental insurance
- Life insurance
- Disability insurance
- 14 paid company holidays