Ferryscanner is an online search and booking engine that helps people find affordable ferry tickets to exciting destinations around the world.
Since 2018, we have been simplifying the ferry booking process by offering ferry tickets for more than 900 destinations across the globe in 25 languages.
Our company culture is based on five core values: Ownership, Trust & Respect, Constant Improvement, Customer Obsession, and Being Bold.
At Ferryscanner, data is more than reporting, it is a key enabler of how we build products, make decisions, and leverage AI across the business.
Responsibilities
Design, build, and maintain scalable data pipelines, workflows, and data models.
Own and evolve Ferryscanner’s data architecture, ensuring reliability, quality, security, and accessibility.
Develop and maintain datasets, warehouses, and reporting foundations that support analytics and decision-making.
Partner with the Data Analyst to improve data availability, self-service analytics, and reporting capabilities.
Build and optimize data infrastructure that supports AI and machine learning initiatives.
Establish best practices around data governance, observability, documentation, lineage, and monitoring.
Requirements
At least 4 years proven experience as a Data Engineer, Analytics Engineer, Data Platform Engineer, or similar role, ideally within a product-led, marketplace, travel, or consumer technology business.
Strong SQL and Python skills, with experience building production-grade data pipelines and scalable data models.
Experience with cloud platforms (AWS, GCP, or Azure) and modern data warehouses such as BigQuery, Snowflake, or Redshift.
Hands-on experience with data orchestration and transformation tools such as Airflow, Dagster, dbt, or equivalent.
Strong understanding of data architecture, ETL/ELT processes, data governance, and software engineering best practices.
Experience building reliable monitoring, observability, and quality assurance processes for data systems.
Demonstrated ability to work cross-functionally with Engineering, Product, Analytics, and business stakeholders.
Familiarity with AI and machine learning workflows, including data pipelines that support model training, evaluation, and deployment.
Experience with vector databases, embeddings, retrieval systems, or LLM-powered applications is a strong plus.
Comfortable leveraging AI-assisted development tools and modern engineering workflows.
Strong analytical, problem-solving, and organizational skills, with the ability to balance long-term platform thinking with practical execution.
Conditions
Opportunity to shape and scale Ferryscanner’s data platform and AI foundations at a pivotal stage of growth.
High-impact role with direct influence on product development, business decision-making, and AI adoption.
Collaborative, cross-functional environment spanning Engineering, Product, Analytics, and Business teams.
International team, continuous learning, and exposure to cutting-edge data and AI technologies.
Hybrid working model and additional annual leave days.