About Jorrit:

Jorrit Enzio Posor is a seasoned technology professional, who currently serves as the Tech Lead for the centralized data team at FINN, a fast-growing car subscription company. With his deep-seated passion for utilizing data to drive business growth, he leads a team responsible for defining and maintaining the tooling necessary for data analysts and other data teams to effectively access the data warehouse and gather key performance indicators, reports, and insights. Jorrit also has a deep understanding of data management and a commitment to excellence. He is poised to drive Safin's continued success through innovative and effective data solutions.

Synopsis:

In this episode of The Technology Leadership Podcast, Jorrit discusses the Data Mesh strategy that aligns both the technical and organizational aspects of data management. He shares the bottlenecks caused by the traditional centralized data team structures and explains how a Data Mesh solves this by decentralizing data teams, with each department having its own data team. The centralized data team builds a platform for the decentralized teams to use and focuses on bringing engineering knowledge and capabilities closer to each department. Software-as-a-service (SaaS) tools such as Fivetran and Google BigQuery are combined with a data mesh approach to manage this data architecture and prevent technical debt. Jorrit also explains data analytics and management using this structure before getting into the business benefits of it.

Key Takeaways:

• Jorrit discusses the Data Mesh concept, which is about aligning the technical and organizational aspects of data teams.
• When does a centralized data team become a bottleneck? How can you overcome the challenge? When a centralized data team receives too many requests from different departments, it becomes a challenge to use. The solution is to decentralize data teams, and assign each department with its own data team. The infrastructure can still stay centralized.
• Central data teams can provide support to decentralized teams and aid in faster speed of execution and shipping of insights.
• Use a combination of Fivetran, Google BigQuery, and DBT to manage data from multiple sources.
• The most important aspect of building a data platform is focusing on the central data team and balancing centralization and decentralization.
• An essential business benefit of using a decentralized data team is being able to avoid bottlenecks in shipping insights and having data that accurately reflects changes in the business.
• You can determine if a data mesh is the right strategy for you by understanding the trade-offs involved. This can be done by evaluating your current problems and future growth plans.

Episode Outline:

[00:37] Meet Jorrit
[01:48] What is meant by scaling a decentralized organization?
[03:12] How data mesh impacts data and other business teams
[07:03] The benefits of decentralized data teams in business
[08:55] How to implement decentralized data teams in your company and the bottlenecks to centralized data teams
[16:37] How Jorrit implemented decentralized data teams in his company
[24:31] 3/4 things Jorrit would’ve told himself a year ago that would help him become more successful 
[27:32] How can a technical lead communicate the benefits of a decentralized data team in his company?
[30:18] One piece of advice Jorrit would like to leave you with