Senior Data Engineer

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.  

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

THE POSITION
Our roster has an opening with your name on it

Our competitive edge comes from making decisions based on accurate and timely data. As a Senior Data Engineer in Core Data Infrastructure, you will work alongside other engineers to ensure the proper upkeep of our analytic platforms within the FanDuel organization by establishing platform governance and feature improvements to enable the business.

Collaboration is at the core of your role. You will have established analytic engineer capabilities as well as enablement skills to allow for data process excellence in the organization. In this role, you will be working closely with the data users across the organization to ensure the adoption of platform best practices. You’ll also be expected to influence the team to invent, evolve, and/or deprecate data solutions.

You should have a passion for imparting knowledge by working with analysts to improve data processes and to minimize areas of risk across our platforms. You will show a pragmatic approach to problem-solving; your experience should be built on a solid foundation of engineering development and analytic best practices.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

• Lead regular design and code reviews to enforce development best practices and ensure high-quality, maintainable pipelines across the team.
• Monitor and optimize job and query performance in Databricks and Airflow, identifying bottlenecks and implementing scalable solutions.
• Contribute to the architecture and design of modern data platform solutions leveraging Databricks and Airflow, with a focus on performance, scalability, and cost-efficiency.
• Author and maintain clear documentation on pipeline architecture, operational workflows, data models, and platform configurations.
• Partner with leadership to drive adoption of modern platform features and implement data governance standards across the organization.
• Design and implement production-grade data pipelines for real-time and batch workloads, including infrastructure and operational monitoring.
• Mentor junior engineers by promoting platform best practices, sharing design patterns, and encouraging innovation and ownership.
• Communicate platform insights and improvements through dashboards, models, or concise reports that help stakeholders make data-driven decisions.
  
  
  

THE STATS
What we're looking for in our next teammate

• 5+ years of development experience in a core programming language, preferably Python, with strong skills in coding, debugging, and testing.
• 5+ years of hands-on experience with Databricks or an equivalent big data platform (e.g., GCP BigQuery, AWS Redshift), including:
  • Building and optimizing ETL/ELT pipelines in Delta Lake or similar data lake formats.
  • Familiarity with Unity Catalog, SQL Warehouses, and performance tuning in Databricks.
• 5+ years of experience using Apache Airflow (preferably with Astronomer or MWAA), including:
  • Designing modular, idempotent, production-ready DAGs.
  • Experience with dynamic DAG generation, task retries, and sensor management.
• Strong experience working in cloud environments like AWS, Azure, or GCP, including:
  • Proficiency in cloud-native services such as S3, IAM, Lambda, EventBridge, and Secrets Manager.
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