Data Engineer, TravelPerk

• 3+ years of relevant experience as a Data Engineer, Business Intelligence, Big-Data Engineer or similar role working with large-scale data systems
• Excellent communication skills, both written and spoken, in English
• You are a Master in SQL, optimizing queries for performance, scalability, and ease of maintenance
• You feel comfortable querying different types of databases (PostgreSQL, Redshift, Snowflake) and have knowledge of different AWS services
• You’re an ace at data modeling, accustomed to designing and implementing complex architectures with a constant eye on their future evolution while taking into account the needs of multiple users
• You have experience building data pipelines using Python
• You have experience integrating data from multiple sources including DBs, product tracking, and APIs. You get excited by seeing your jobs run like clockwork
• You have an instinct for automation
• You have the desire to work in an international environment, with minimal direction, and with highly engaged individuals

Desirable

• We are looking for a Data Engineer to scale our Data Operations team and help us improve our Data Governance & Data Integration processes
• Ensure we are able to keep all data in our DWH updated and accessible for analysis
• Partner with the Data analysts to support the requirements of the company in terms of analytics, reliability and efficiency
• Develop and maintain data pipelines to extract data from different sources and integrate it in the DWH following data modeling best practices
• Take charge of the required data processing while ensuring sustainable and organic growth of the data model and the infrastructure
• Keep our data infrastructure up to date and working like a clock
• Integrate and model datasets from different sources
• Support our Data Analysts & BI Developers to get the right data to build awesome dashboards and complex analytical models
• Support Product and Analytics teams in defining the best approaches for data modeling
• Use data to investigate and help resolve issues in our product or processes
• Proactively suggest improvements to data reliability, efficiency and quality
• Champion a healthy data culture throughout the organization