Staff Data Engineer

FanDuel•Jersey City, NJ

1d•Hybrid

About The Position

Our roster has an opening with your name on it We are seeking a Staff Data Engineer to lead the technical design and implementation of our most critical data infrastructure and products. In this senior-level individual contributor role, you’ll be responsible for designing scalable systems, setting data architecture standards, and solving complex technical challenges that power analytics, data science, and business function use cases across the company. You will work closely with engineers, product managers, and business stakeholders to architect data solutions that are performant, reliable, and built with a long-term, customer-centric mindset. 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.

Requirements

8+ years of experience in data engineering or a related field, with a focus on building scalable data systems and platforms that support ML, Analytics and AI use cases.
Strong expertise in modern data tools and frameworks such as Spark, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure)
Deep understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures
Proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
Demonstrated experience owning complex technical systems end-to-end, from design through production
Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences

Nice To Haves

Experience designing data platforms that support analytics, machine learning, and operational workload
Familiarity with data governance, privacy, and compliance frameworks
Background in customer-centric or product-driven environments (e.g., digital, eCommerce, SaaS)
Experience with infrastructure-as-code and data platform observability (e.g., Terraform)

Responsibilities

Design and implement scalable, maintainable, and secure batch & streaming data pipelines and architectures that support enterprise-wide data needs
Define standards for data modeling, data product design, and pipeline orchestration using modern tools and cloud-native technologies
Collaborate with cross-functional stakeholders to translate business and analytical requirements into end-to-end data solutions
Establish and enforce engineering best practices around code quality, testing, documentation, and deployment
Contribute to the evolution of the data platform, ensuring systems are modular, interoperable, and resilient
Lead technical design and code reviews, mentoring peers and raising the bar for engineering excellence
Partner with data platform teams, analytics, and data science to deliver reusable data assets and shared infrastructure
Identify and resolve architectural bottlenecks in the current data platform and propose improvements that reduce complexity and boost performance
Drive initiatives that improve data quality, lineage, observability, and system reliability
Act as a technical liaison between engineering, product, and analytics teams, ensuring alignment on architecture and data strategy
Provide technical leadership and guidance to other data engineers and contribute to the team’s overall growth and maturity
Help evaluate and onboard new technologies, frameworks, and practices to keep our stack modern and efficient