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Data Engineer
FanDuel — крупный международный бренд с отличным соцпакетом и современным стеком. Работа в такой компании дает отличные возможности для карьерного роста и работы с по-настоящему большими данными.
Сложность вакансии
Роль требует уверенного владения современным стеком (Databricks, Spark, Airflow) и навыков работы с облачными платформами. Высокий темп работы в индустрии ставок и гейминга добавляет сложности в плане ответственности за точность данных.
Анализ зарплаты
Предлагаемая позиция в Эдинбурге соответствует рыночным стандартам для опытных инженеров данных. В Великобритании зарплаты в финтехе и гейминге обычно находятся в верхнем дециле рынка.
Сопроводительное письмо
I am writing to express my interest in the Data Engineer position at FanDuel. With a strong background in building scalable data pipelines and working with modern tech stacks like Spark, Airflow, and Databricks, I am confident in my ability to contribute to your growing data engineering team. My experience in translating complex business requirements into robust engineering solutions aligns perfectly with the 'Game Plan' outlined in your job description.
Throughout my career, I have focused on ensuring data reliability and performance at scale, which I know is critical for a premier mobile gaming company like FanDuel. I am particularly drawn to this role because of the opportunity to work within a dynamic, agile environment and contribute to products that millions of fans love. I am eager to bring my technical expertise in Python and SQL, along with my passion for data modeling, to help drive FanDuel's data-driven decision-making process.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в fanduel уже сейчас
Присоединяйтесь к лидеру индустрии спортивных развлечений и создавайте высоконагруженные системы данных вместе с FanDuel!
Описание вакансии
THE POSITION
Our roster has an opening with your name on it
We are looking for a Data Engineer to join our growing data engineering team and help build the pipelines and infrastructure that power analytics, machine learning, and business decision-making across the company. In this role, you’ll contribute to the design, development, and maintenance of reliable data systems while collaborating with stakeholders to support high-impact data use cases.
The ideal candidate is a strong technical contributor who enjoys working with data at scale, solving practical problems, and continuously learning in a fast-paced environment. If you’re excited by this challenge and want to work within a dynamic company, then we’d love to hear from you.
THE GAME PLAN
Everyone on our team has a part to play
Build & Maintain Data Pipelines
- Design, build, and maintain scalable batch and streaming data pipelines to support analytics and business operations.
- Write clean, efficient, and well-documented code using tools like Python, SQL, and Spark.
- Ensure data is reliable, accurate, and delivered in a timely manner
Collaborate Across Teams
- Work with data analysts, data scientists, and product managers to understand requirements and deliver actionable data solutions
- Translate business questions into engineering tasks and contribute to technical planning.
- Participate in code reviews, sprint planning, and retrospectives as part of an agile team.
Data Quality & Operations
- Monitor data pipelines and troubleshoot issues in a timely, systematic manner
- Implement data quality checks and contribute to observability and testing practices
- Document data sources, transformations, and architecture decisions to support long-term maintainability
THE STATS
What we're looking for in our next teammate
- Experience in data engineering, analytics engineering, or software engineering with a focus on data.
- Strong SQL skills and familiarity with at least one programming language (e.g., Python, Java, or Scala).
- Hands-on experience with modern data tools such as Databricks, Airflow, DBT, Spark, or Kafka.
- Understanding of data modeling concepts, data warehousing, and ETL/ELT best practices.
- Experience working with cloud-based data platforms (AWS, GCP, or Azure).
Preferred Qualifications
- Experience supporting BI, analytics, or data science teams.
- Familiarity with version control, CI/CD, and collaborative development workflows.
- Exposure to data governance, privacy, or compliance practices.
- Eagerness to learn new technologies and contribute to the growth of the team.
PLAYER BENEFITS
We treat our team right
From our many opportunities for professional development to our generous insurance and paid leave policies, we’re committed to making sure our employees get as much out of FanDuel as we ask them to give. Competitive compensation is just the beginning. As part of our team, you can expect:
- An exciting and fun environment committed to driving real growth
- Opportunities to build really cool products that fans love
- Career and professional development resources to help you refine your game plan for owning and driving your career and development
- Be well, save well and live well - with FanDuel Total Rewards your benefits are one highlight reel after another
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).
Diversity, Equity and Inclusion
FanDuel is an equal opportunities employer. Diversity and inclusion in FanDuel means that we respect and value everyone as individuals. We don't tolerate bias, judgement or harassment. Our focus is on developing employees so that they reach their full potential.
FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.
The requirements listed in our job descriptions are guidelines, not hard and fast rules. You don’t have to satisfy every requirement or meet every qualification listed. If your skills are transferable and you are in the ballpark experience-wise, we'd love to speak to you!
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Навыки
- Python
- SQL
- Spark
- Databricks
- Airflow
- dbt
- Kafka
- AWS
- GCP
- Azure
- ETL
- Data Modeling
- CI/CD
Возможные вопросы на собеседовании
Проверка практического опыта работы с большими данными и оптимизации процессов.
Расскажите о самом сложном конвейере данных (pipeline), который вы разработали. С какими проблемами производительности вы столкнулись и как их решили?
Оценка навыков проектирования архитектуры данных.
Как бы вы спроектировали ETL-процесс для обработки потоковых данных в реальном времени для системы ставок, где задержка критична?
Проверка владения ключевым инструментом из описания вакансии.
В чем разница между использованием управляемого Spark в Databricks и ванильного Spark в облаке? Какие преимущества это дает инженеру?
Оценка понимания качества данных и процессов мониторинга.
Какие метрики и проверки качества данных вы считаете обязательными для внедрения в продакшн-пайплайны?
Проверка умения работать в кросс-функциональной команде.
Опишите случай, когда требования аналитиков или дата-сайентистов были технически трудновыполнимы. Как вы нашли компромисс?
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