Data Platform Engineer

We are looking for a Data Platform Engineer to support that foundation. You will join our Platform team, which is responsible for the infrastructure, automation and developer experience that underpin all engineering at FAIRTIQ. You will drive the development of our data platform: the tooling that enables squads to operate their pipelines and storage, amongst others. This is a driving role, not a maintenance role: there is an existing platform, a legacy platform to retire, and much still to design and build.

You will flourish in this role if you:

• Have built and operated production data platforms, and think of data as a product with consumers, contracts and SLAs
• Have designed and operated internal developer platforms
• Enjoy solving complex problems that enable other engineers and analysts to move faster and safer
• Have experience with cloud data infrastructure, pipeline orchestration, and infrastructure automation (e.g. Terraform)
• Like thinking in terms of systems, abstractions, and automation
• Care deeply about data quality and cost efficiency, and know that undetected bad data is worse than no data
• Believe that quality and security are not just requirements, but essential attributes of a sustainable engineering culture
• Want to grow beyond data into broader cloud platform engineering, and to bring your team along with you

Role Responsibilities

• Drive FAIRTIQ data platform development - ingestion, storage, transformation and access - as a self-service product for the whole company
• Support the migration from our legacy data infrastructure to the new platform, and decommission the old one
• Provide batch and streaming platform capabilities
• Setup building blocks for data quality, freshness and lineage, with monitoring and alerting that people act on
• Manage data infrastructure as code, deployed through our existing CI/CD and GitOps pipelines
• Build data governance into the platform: retention, access control, pseudonymisation and audit trails that meet GDPR and our operator contracts
• Optimise system performance, cost efficiency and resiliency
• Grow data platform capability across the Platform squad through documentation, pairing and Dojo sessions
• Contribute to Squad-owned topics beyond data, and take part in incident response and postmortems
• Collaborate with backend, mobile and analytics colleagues so platform solutions fit real product and engineering needs, At FAIRTIQ, we believe that our employees are our biggest asset. A healthy culture, based on respect, inclusion, diversity and individual empowerment is the key to our success story.
• Dynamic and international work environment
• Chance to be part of a fast growing, international startup
• Budget and support for self-improvement
• Creativity and innovation boosters with our “Tech Joker Days” (work on whatever you think may help FAIRTIQ)
• Lots of leadership opportunities (tech, people)
• Flexible working hours & fully remote work

Recruitment Process

• Screening interview with Pedro (from the People Team): ~45 minutes
• Tech Screening & Problem Solving interview: 90 minutes
• Platform Engineering interview: 60 minutes
• Data Engineering interview: 60 minutes

• BSc or MSc in Computer Science, Software Engineering or a related field
• At least 5 years of professional experience as a Data Platform Engineer or Data Engineer
• Strong Python skills, and the ability to write clean, maintainable, well-tested code
• Proficiency with cloud platforms (preferably AWS) and with data services on them
• Hands-on experience with pipeline orchestration and with a data transformation framework
• Experience with streaming, ideally Kafka - able to reason about ordering, delivery guarantees and schema evolution
• Experience with Terraform or similar infrastructure-as-code tools
• Awareness of data protection obligations (GDPR) and how they translate into platform design
• Proactive, organized, and communicative - you enjoy collaborating across disciplines and sharing what you know
• Excellent English communication skills
• EU based

Nice to have

• Kubernetes and container orchestration experience
• Experience with Open table formats (e.g. Iceberg) or LakeHouse architecture in production
• Experience supporting ML or AI workloads: feature pipelines, training data, model monitoring
• Background in a regulated, financial or mobility domain where correctness had to be auditable
• Experience being the person who made a data platform self-service for others

As FAIRTIQ continues to grow, so does the volume and importance of the data we generate. Supporting more than one million monthly active users and millions of public transport journeys generates the data that determines what passengers pay, what transport operators receive and how the public transport network can be improved. Reliable, high-quality data is the foundation for better insights and faster decision-making.