Senior Data Engineer

@ FanDuel

About FanDuel Group

FanDuel Group is a world-class team of brands and products that deliver sports betting, gaming and entertainment to millions of US sports fans every day. They foster a culture where everyone can succeed, offering career progression, financial security, and a sense of belonging.

The Position

We are seeking a Senior Data Engineer to design and build scalable, reliable, and high-quality data solutions that empower analytics, machine learning, and business operations. This role requires a hands-on contributor who will help shape the technical foundation of our data ecosystem, collaborating closely with engineers, analysts, product managers, and data scientists.

The Game Plan

Build & Maintain Data Infrastructure:

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Work with large, complex datasets ensuring data cleanliness and accessibility.
• Develop and maintain batch and streaming pipelines using modern tools.

Deliver High-Quality, Reusable Solutions:

• Create modular, reusable data models with tools like Spark or dbt.
• Collaborate with stakeholders to translate business needs into solutions.
• Ensure data quality and consistency through validations and monitoring.

Contribute to Engineering Excellence:

• Follow best practices in testing, version control, code reviews, and documentation.
• Participate in technical design and architecture reviews.
• Help evolve our data platform to improve performance and scalability.

Collaborate & Communicate:

• Partner with data scientists, analysts, and product managers for data-driven decisions.
• Clearly communicate technical concepts, project status, and risks.
• Mentor junior engineers through collaborative problem-solving and code reviews.

The Stats

Candidates should have 5+ years of data or software engineering experience focused on data pipelines, strong SQL skills, proficiency in programming languages like Python, Scala or Java, and hands-on experience with modern data tools (Airflow, Spark, dbt, Kafka, or Databricks). Familiarity with cloud-based platforms (AWS, GCP, Azure) is required. Preferred skills include supporting analytics and machine learning workflows, understanding data governance and compliance, and experience with infrastructure-as-code practices.

Player Contract

Enjoy a dynamic work environment that offers professional development, competitive compensation, flexible vacation policies, and comprehensive benefits. Embrace an inclusive culture where diversity is celebrated and all employees are valued.

Key skills/competency

• Data Engineering
• ETL/ELT
• SQL
• Python
• Spark
• dbt
• Cloud Platforms
• Data Modeling
• Data Quality
• Collaboration