Principal Data Engineer - FanDuel, Hybrid
About Betfair Romania Development:
Betfair Romania Development is the largest technology hub of Flutter Entertainment, with over 2,000 people powering the world’s leading sports betting and iGaming brands. Exciting, immersive and safe experiences are delivered to over 18 million customers worldwide, from our office in Cluj-Napoca. Driven by relentless innovation and commitment to excellence, we operate our own unbeatable portfolio of diverse proprietary brands such as FanDuel, PokerStars, SportsBet, Betfair, Paddy Power, or Sky Betting & Gaming.
Our Values:
The values we share at Betfair Romania Development define what makes us unique as a team. They empower us by giving meaning to our contributions, and they ensure that we consistently strive for excellence in everything we do. We are looking for passionate individuals who align with our values and are committed to making a difference.
Win together | Raise the bar | Got your back | Own it | Positive impact
About FanDuel:
FanDuel is a leading force in the sports-tech entertainment industry, redefining how fans engage with their favourite sports, teams, and leagues. As the premier gaming destination in North America, FanDuel operates across multiple verticals, including sports betting, daily fantasy sports, online gaming, advance-deposit wagering, and media.
Role Overview:
We are looking for a Principal Data Engineer to design and build scalable, reliable, and high-quality data solutions that power analytics, machine learning, and business operations. You’ll be a hands-on contributor who plays a key role in shaping the technical foundation of our data ecosystem.
As a senior member of the team, you’ll work closely with engineers, analysts, product managers, and data scientists to deliver data pipelines and platforms that drive meaningful business outcomes. The ideal candidate is a strong problem solver, a team player, and someone who brings both technical depth and a collaborative mindset to every challenge.
Key Accountabilities & 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 engineering, 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
Drive Engineering Best Practices
- 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
Lead Strategic Initiatives
- Partner with other data engineering 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
Influence and Collaborate Across Teams
- 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
Build & Maintain Data Infrastructure
- Design, develop, and maintain scalable ETL/ELT pipelines to support data products, analytics, and operational systems
- Work with large-scale, complex datasets and ensure data is clean, well-modelled, and accessible across the organization
- Develop and maintain batch and streaming data pipelines and data platforms using modern tools and technologies
Deliver High-Quality, Reusable Solutions
- Build modular, reusable data models and assets using tools like Spark, dbt or similar frameworks
- Collaborate with stakeholders to understand business needs and translate them into reliable, production-ready data solutions
- Ensure data quality, accuracy, and consistency through validation frameworks and monitoring
Contribute to Engineering Excellence
- Follow and promote software engineering best practices, including testing, version control, documentation, and code reviews
- Actively participate in technical design discussions, and architecture reviews
- Help evolve our data platform and tooling to improve performance, developer experience, and scalability
Collaborate & Communicate
- Partner with data scientists, analysts, and product managers to support data-driven decision-making.
- Clearly communicate technical concepts, project status, and risks to stakeholders
- Share knowledge and mentor junior engineers through code reviews and collaborative problem-solving
Skills, Capabilities & Experience Required
Essential:
- 8+ years of experience in data engineering or a related field, with a focus on building scalable data systems and platforms.
- Strong expertise in modern data tools and frameworks such as Spark, dbt, 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
- Experience of database performance analysis and design
- Unit testing knowledge
- Exposure to Continuous Integration / Continuous Delivery tools (e.g. Go, Jenkins)
- Strong problem-solving skills and ability to work independently in a fast-paced environment.
Desirable:
- Experience working in Agile environments
- Experience supporting analytics and machine learning workflows.
- Familiarity with data governance, privacy, and compliance frameworks.
- Experience working in a product-led or customer-centric organization.
- Familiarity with infrastructure-as-code or DevOps practices related to data systems.
Benefits:
- Hybrid & remote working options
- €1,000 per year for self-development
- Company share scheme
- 25 days of annual leave per year
- 20 days per year to work abroad
- 5 personal days/year
- Flexible benefits: travel, sports, hobbies
- Extended health, dental and travel insurances
- Customized well-being programmes
- Career growth sessions
- Thousands of online courses through Udemy
- A variety of engaging office events
Disclaimer:
We are an inclusive employer. By embracing diverse experiences and perspectives, we create a lasting, positive impact for our employees, customers, and the communities we’re part of. You don't have to meet all the requirements listed to apply for this role. If you need any adjustments to make this role work for you, let us know, and we’ll see how we can accommodate them.
We thank all applicants for their interest; however, only the candidates who best meet the job requirements will be contacted for an interview.
By submitting your application online, you agree that your details will be used to progress your application for employment. If your application is successful, your details will be used to administer your personnel record. If your application is unsuccessful, we will retain your details for a period no longer than three years, to consider you for prospective roles within the company.
