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Data Engineering Manager

FanDuel
CompanyFanDuel
CategoryEngineering
LocationNew York City
RemoteOn-site (inferred)
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted23 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
THE POSITION Our roster has an opening with your name on it We are seeking a  Data Engineering Manager  to lead a team of data engineers in building high-quality, scalable data products and infrastructure. In this hybrid role, you’ll balance people management with technical delivery—mentoring engineers, guiding solution design, and collaborating across teams to deliver data systems that support analytics, data science, and operational needs. This role is ideal for an experienced data engineer or tech lead who is ready to take the next step into engineering management and enjoys blending hands-on support with strategic execution. If you’re excited by this challenge and want to work within a dynamic company, then we’d love to hear from you. 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 Team Management & Growth Lead a team of data engineers through coaching, mentorship, and technical guidance Support individual career development and performance feedback, creating growth opportunities for your team Foster a collaborative, inclusive, and high-performance team culture Technical Oversight & Delivery 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 Cross-Functional Collaboration 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 Operational Excellence 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   THE STATS What we're looking for in our next teammate 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). Strong communication and collaboration skills with a passion for working across teams.   Preferred Skills 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 Experience working in a product-driven, customer-focused organization Understanding of data privacy, security, and compliance frameworks   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 dis
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