Analytics Engineering with dbt: A FinTech application

N26, a neo-bank from Germany, has successfully integrated the Data Build Tool (dbt) into its data architecture, significantly enhancing the productivity and scope of its Data Analytics team. Initially, N26 faced challenges related to data governance and pipeline management, relying on in-house ETL solutions that required analysts to code using Python and SQL. However, with dbt, which supports SQL-based data transformation pipelines, N26 streamlined its data processes, allowing analysts to focus on building and maintaining core data models without needing extensive SQL admin expertise. The adoption of dbt has led to the creation of complex data projects, with over 800 models running regularly, and has fostered a more autonomous data analytics environment. Despite some challenges related to data architecture knowledge and dependency management, dbt has proven integral to N26's data strategy, prompting plans to hire analytics engineers and explore tools like Airflow to further improve workflow orchestration and data quality.

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