About the job
Join Our Team as a Data Engineer!
At FanDuel, we are excited to announce an opportunity for a Data Engineer to join our expanding data engineering team. In this pivotal role, you will be instrumental in designing, developing, and maintaining the robust data pipelines and infrastructure that underpin analytics, machine learning, and strategic business decisions across our organization. Collaborating closely with various stakeholders, you will support impactful data initiatives and ensure that our data systems are efficient and reliable.
The ideal candidate is a proactive technical expert with a passion for working with large-scale data, adept at solving real-world challenges, executing projects independently, and eager to learn in a fast-paced setting. If you are enthusiastic about this opportunity and want to thrive within a vibrant company culture, we would love to hear from you!
Your Responsibilities:
Build & Maintain Data Pipelines:
- Design, implement, and manage scalable batch and streaming data pipelines to support analytics and operational needs.
- Create clean, efficient, and well-documented code using technologies such as Python, SQL, and Spark.
- Guarantee the reliability and timely delivery of accurate data.
- Lead initiatives to enhance and develop well-defined data products.
Collaborate Across Teams:
- Engage with data analysts, data scientists, and product managers to clarify requirements and deliver actionable data solutions.
- Translate business inquiries into engineering tasks and contribute to technical project planning.
- Participate in code reviews, sprint planning, and retrospectives as part of an agile team.
- Contribute to the establishment of best practices across the team.
Ensure Data Quality & Operations:
- Monitor data pipelines and promptly troubleshoot any issues that arise.
- Drive the reliability and continuous enhancement of our data platforms and pipelines.
- Implement data quality checks and engage in observability and testing practices.
- Document data sources, transformation processes, and architectural decisions to support long-term maintainability.

