Brice consulted for my group within Spotify for 2+ years, essentially acting as an extension of my team by delivering high priority projects at times when we did not have enough internal resourcing to quickly take advantage of opportunities. That included automating workflows between Spotify and external partners, that allowed us to scale new business and revenue streams quickly and efficiently; creating integrations with software products to enable my team to quickly understand and analyze business performance; Brice's team also conducted code refactoring work for us to improve our own software performance. Brice's commitment to our business was such that he and his group felt like a part of our group, helping us achieve our goals at every step of the way. We look forward to continuing to work with Brice in the future. -- Rene Volker, Senior Director, Live Events, Spotify
We were retained by Spotify's Live Event Bet as their embedded analytics engineering team. The Live Events team was principally focused on recommending concerts to users, primary ticketing, and concert promotion and management.
Our first task was the development of a "first of it's kind" venue database. This dataset was used to better understand the market dynamics involved in a user's decision to purchase a ticket and attend a concert.
Eventually, our team grew and we were asked to take on additional operational data activities. In this expanded role, we created an automated payment & reconciliation solution for vendors (e.g. venues) that removed hundreds of hours of manual work a week. We also built out a large-scale integration with Hubspot and their internal systems that facilitated inbound lead management, as well as metrics and reporting.
On the technical side, we worked with a mix of python, SQL, and dbt via BigQuery. We used plenty of tools that are specific to the Spotify ecosystem like Backstage, Tingle, Flyte, and Luigi. Some of our code is still used today to power concert recommendations via email and push notifications to millions of users on a daily basis.