Staff 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

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.

As a valued member of the Data Engineering Team, the Staff Data Security Engineer will be responsible for implementing and maintaining secure data infrastructure, ensuring compliance with FanDuel and industry standards and regulations. Your expertise in compliance frameworks, coupled with your technical skills in Python, SQL, GitHub, Redshift, Databricks, and dbt, will be instrumental in driving the success of FanDuel's data security initiatives. You will work closely with various stakeholders, including data engineers, data analysts, and security professionals, to design and implement secure data pipelines, analyze security risks, and enhance overall data protection. The ability to work across organizations, a detailed approach and a passion for documentation are musts!

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

• Design, develop and maintain secure data infrastructure, including designing and implementing data pipelines, ETL processes, and data access controls.
• Collaborate with cross-functional teams to ensure compliance with relevant industry standards and compliance regimes (e.g., SOX, ISO, NIST etc.), including conducting regular audits and risk assessments.
• Implement and maintain data encryption, tokenization, and access control mechanisms to protect sensitive data.
• Utilize Python, SQL, GitHub, Redshift, Databricks, and dbt to design and secure data models, queries, and data integration workflows.
• Collaborate with FanDuel security teams to identify and mitigate potential vulnerabilities and security risks within data systems and infrastructure.
• Stay updated with the latest industry trends, tools, and technologies related to data security and compliance, and make recommendations for process improvements and enhancements.
• Participate in agile development practices, including sprint planning, daily stand-ups, and retrospectives, to ensure timely and efficient project delivery.
• Collaborate with data engineers to support data initiatives, providing insights and guidance on data security and compliance.
• Conduct training sessions, create and share learning materials to educate the engineering teams within and outside of data organization and make them aware of the do’s, don’ts and the latest developments to secure the data infrastructure.
  
  
  

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

• Bachelor's degree in Computer Science, Information Systems, or a related field.
• 7+ years of Data Security Engineer or a similar role, with a strong focus on data security and compliance.
• In-depth knowledge of compliance frameworks and regulations, such as SOX, ISO, NIST, GDPR etc.
• Proficiency in programming languages such as Python and SQL, with experience in leveraging these languages for data engineering tasks.
• Strong experience with version control systems like GitHub and working collaboratively in a team environment.
• Hands-on experience with cloud-based data platforms, such as Redshift and Databricks.
• Proven experience with AWS services, particularly IAM (Identity and Access Management).
• Familiarity with dbt (data build tool) and its application in data modeling and transformation.
• Understanding of data encryption, tokenization, and access control mechanisms.<