FanDuel is looking to design and build the next generation of their data solutions by hiring a Senior Staff Data Engineer to architect scalable data platforms and pipelines, develop reusable data products, and partner with cross-functional teams to solve complex, data-driven problems.
Requirements
- 10+ years of experience in data engineering or software engineering, with a focus on building data platforms and pipelines at scale
- Expertise in modern data technologies (e.g., Spark, Airflow, dbt, Kafka, Fivetran, Databricks) and cloud platforms like AWS, GCP, or Azure.
- Strong command of SQL and at least one programming language (e.g., Python, Scala, Java).
- Deep experience designing data models, data products, and ETL/ELT workflows for large, complex datasets.
- Proven ability to lead technical projects end-to-end, from architecture to implementation and operationalization
- Experience building data platforms in a product-driven or DTC organization
- Knowledge of ML/AI data infrastructure and supporting machine learning workflows in production
Responsibilities
- Design and implement robust, scalable, and maintainable data pipelines and platform components using modern data stack tools and cloud infrastructure
- Define and enforce architectural standards, data modeling best practices, and data quality frameworks
- Drive the development of reusable, modular data products that serve multiple analytical and operational use cases
- Serve as a technical mentor and role model for other engineers, providing guidance on system design, performance optimization, and best practices
- Lead design reviews, contribute to critical design and architecture decisions, and set coding standards across the team
- Identify gaps and opportunities in the existing data platform and propose scalable improvements that drive business value
- Lead efforts in observability, monitoring, and reliability for our data pipelines and infrastructure
Other
- Exceptional communication and collaboration skills, with a track record of influencing stakeholders across engineering, product, and analytics teams
- Contributions to open-source projects or engineering blogs is a plus
- LI- Hybrid
