Senior Data Engineer (Airbyte - BigQuery - dbt - python - Looker)

We are Qover, a leading insurtech scale-up that has raised 100 million. With an international team of 160+ colleagues based in Brussels and beyond, we help companies orchestrate digital embedded insurance experiences - creating meaningful connections with their community and enabling their success. Since Qover was founded in 2016, our co-founders have had a clear vision of the future of insurance: it must be simple, transparent, and accessible across borders - a global safety net. Our platform protects 15M+ users across 32 European countries and works with longstanding partners like Revolut, Mastercard, BMW, Canyon, and Monzo, among many others. .Visit our website for more about what we do

In the Qover data team, we are engineers at heart with a strong focus on operations. We are supporting the executions of our insurance programs on a daily basis by ensuring that all our partners have access to fresh and reliable data. We are seeking a Senior Data Engineer to strengthen our data capabilities. You will be in the driver's seat for implementing data reports, from prototyping to production, while always ensuring that your technical solutions align with the best engineering practices. Our data stack (high-level): Airbyte - BigQuery - dbt - python - Looker Your tasks and responsibilities Your main objective is to develop and maintain scalable and clean data financial reports to support the launch and execution of our insurance programs. We expect you to: develop, maintain and improve our dbt data pipelines that support the day-to-day operations of our embedded insurance programs propose and implement a robust data model that can cope with the specificities of insurance data and require little modification to support the launch of the new products make sure that the data is delivered timely to our partners run quality assurance checks to ensure data consistency across data deliverables leverage synergies across our data sources to limit the number of tables in our BigQuery data warehouse, and avoid that our databases turn into a data maze Further develop our data governance through extensive testing ( data tests, unit tests, anomaly detection) sufficient data docume