Data Engineer
Listed on 2025-11-20
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IT/Tech
Data Engineer
Location: City of Edinburgh
Fan Duel Edinburgh, Scotland, United Kingdom
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PositionAt Fan Duel Group, we give fans a new and innovative way to interact with their favorite games, sports, and teams. We’re dedicated to building a winning team and we pride ourselves on creating a culture that brings out the best work. We believe in winning right by never compromising on care for our teammates.
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 design scalable systems, set data architecture standards, and solve 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.
Responsibilities Architect High‑Impact Data Systems- 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
- 8+ years of experience in data engineering or a related field, focusing on building scalable data systems and platforms
- Strong expertise in modern data tools and frameworks such as Kafka, Spark, Databricks, dbt, Airflow, and cloud‑native services (AWS, GCP, or Azure)
- Deep understanding of streaming architectures, distributed systems, ETL/ELT pipelines, and data modeling
- Proficiency in at least one object‑oriented programming language (e.g., Python, Java, Scala) and SQL
- 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
- Experience designing data platforms that support analytics, machine learning, and operational workloads
- 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 tools (e.g., Terraform)
Fan Duel Group is the premier mobile gaming company in the United States and Canada. Fan Duel Group consists of a portfolio of leading brands across mobile wagering including America’s #1 Sports book, Fan Duel Sports book; its leading iGaming platform, Fan Duel Casino; the industry’s unquestioned leader in horse racing and advance‑deposit wagering, Fan Duel Racing; and its daily fantasy sports product.
In addition, Fan Duel Group operates Fan Duel TV, its broadly distributed…
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