Forecasting demand for thousands of fashion items across 20 brands is hard. Doing it with siloed, inconsistent data is nearly impossible. At Bestseller, Ivica Kolenkaš and his team solved this by building a self-service data analytics platform grounded in “strong opinions, held loosely”: clear engineering standards balanced with flexibility.

With a team of just three engineers, they built, rebuilt, and now operate a platform serving more than 1,000 users across data engineering, data science, and commercial roles.

This talk shares how the team applied DevOps principles and software engineering practices to Terraform, Snowflake, dbt, and Airflow to create reusable, trustworthy data products at scale. Attendees will learn the architectural decisions that worked, the ones that did not, and how maintaining firm-but-flexible opinions helped the team survive fast growth, changing requirements, and the realities of enterprise data.