At Hostelworld (Permanent), in Porto, Portugal
Salary: €45.000 - €50.000
Expires at: 2025-05-19
Remote policy: Full remoteABOUT US
Hostelworld Group, the global hostel-focussed online booking platform, inspires adventurous minds to meet the world and come back with life-changing stories to tell. Our customers are not your average tourists, they crave cultural connection and unique experiences that we make possible by providing an unbeatable selection of hostels in unmissable locations - all in the palm of their hand.
It is the social nature and community feel of hostels and their environment, that enable travellers to embrace journeys of discovery, adventure and meaning. We have more than 13 million reviews across 17,800 hostels in more than 179 countries, making the brand the leading online hub for social travel. The website operates in 19 different languages and our mobile app in 13 languages.
Founded in 1999 and headquartered in Dublin, Hostelworld has a growing, high-calibre team of 230 people within Technology, Product, Global Markets, HR, Finance & Legal and Marketing Teams across our Dublin, London, Porto, Shanghai and Sydney offices. Hostelworld is listed on the London Stock Exchange and Dublin Euronext.
The Role and Team
The Analytics and Insights team in Hostelworld comprises of 20+ people who provide insights across a number of growth units including paid marketing, customer analytics and app analytics to support decision making at C and senior management level.
As an Analytics Engineer within the Process and Tooling function of the A&I team, you will be in a position to lead the way for how data and analytics is used at HostelWorld. We are seeking a highly skilled and motivated Analytics Engineer with expertise in dbt, Python, and API integrations to join our data team. As an Analytics Engineer, you will play a crucial role in transforming raw data into a well-organized, scalable, and insightful data model that empowers our analytics and business intelligence efforts. You will work closely with data analysts, data scientists, and other stakeholders to ensure the delivery of high-quality, reliable data that drives decision-making across the organization.
Key Responsibilities:
• Data Tooling Team Contribution: Collaborate with the Data Tooling/Data Platform team to design and implement scalable and efficient data models, pipelines, and tools that empower our analytics and data science teams.
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