FanDuel is seeking a Data Engineering Manager to lead a team in building scalable data products and infrastructure to support analytics, data science, and operational needs, specifically partnering with Fraud Operations, Trading Operations, and Risk Product verticals.
Requirements
- 6+ years of experience in data engineering or software engineering, with at least 1–2 years in a team leadership or mentorship role.
- Strong technical background in building and maintaining data pipelines and platforms using tools like Spark, dbt, Airflow, Kafka, or Databricks.
- Proficiency in SQL and one or more programming languages (e.g., Python, Scala, or Java).
- Experience with cloud data platforms (e.g., AWS, GCP, or Azure).
- Prior experience in a people management or tech lead role within a data engineering or analytics team
- Familiarity with machine learning workflows, data observability, and streaming architectures
- Understanding of data privacy, security, and compliance frameworks
Responsibilities
- Lead a team of data engineers through coaching, mentorship, and technical guidance
- Guide the design and implementation of scalable data pipelines, platforms, and data products
- Review architecture and code, provide technical direction, and help resolve complex engineering challenges by being hands-on when needed
- Ensure delivery of high-quality, reliable solutions aligned with business goals and engineering best practices
- Promote operational stability and reliability of data pipelines and systems through monitoring, alerting, and incident response
- Advocate for high standards in data quality, governance, and compliance by collaborating with platform and data governance teams
- Drive continuous improvement in development workflows and team productivity
Other
- Support individual career development and performance feedback, creating growth opportunities for your team
- Foster a collaborative, inclusive, and high-performance team culture
- Partner with product managers, data scientists, analysts, and business stakeholders to understand requirements and prioritize work
- Translate business needs into actionable engineering detailed plans and ensure timely delivery of key projects
- Communicate clearly across technical and non-technical teams to align on priorities and progress
