Data Analytics Engineer - Remote Eligible

Data Analytics Engineer

Ferryhopper is revolutionizing online ferry booking, aiming to change the way people travel by ferry. We are collaborating with more than 180 ferry companies across 35 countries, bringing a fresh and seamless ferry booking experience. We always strive to cater to the needs of all travelers and keep improving our services.

As a Data Analytics Engineer, the main purpose is to leverage data in order to empower the organization to unlock value from multiple data sources.

You will contribute to the design of scalable data pipelines to support Ferryhopper's growing data processing and analytics needs. To achieve this, your day-to-day tasks span from designing and creating data pipelines to collecting, processing, and storing large volumes of data from various sources to create clean, reliable datasets for reporting and analytics. You'll need to be highly motivated, biased for action, have a problem-solving mindset, curiosity, and be passionate about data and enabling data-driven decisions.

The core requirements are:

• Advanced SQL and Python skills
• Solid understanding of data modeling and DWH concepts
• Hands-on experience with a cloud data warehouse, such as BigQuery
• Working experience with dbt or a similar transformation framework

Responsibilities:

• Contribute to the design, build, and maintenance of data pipelines and workflows to ensure reliable and high-quality data across Ferryhopper's data sources, helping to develop clean ingestion and transformation processes.
• Assist in orchestration and monitoring of data flows to guarantee data integrity and freshness across the BI ecosystem.
• Support development and maintenance of data quality checks, including audits, validation logic, and anomaly detection to ensure consistent and reliable data.
• Continuously optimize data collection and reporting workflows, automating manual processes and improving efficiency wherever possible.
• Enable analytics and reporting by delivering well-structured, foundational datasets that support dashboards, reporting, and modeling across the business.
• Perform light data exploration and data serving activities to support analytical and business teams in understanding and utilizing available data.