Free e-Book:The Modern Data Stack:A Technical Roadmap.Download for free now!
Fintech Addi Unlocks New Speed and Insights With Brand New Modern Data Stack

Fintech Addi Unlocks New Speed and Insights With Brand New Modern Data Stack

Case Study: Addi
Juan Martin Pampliega

Posted by Juan Martin Pampliega

on July 17, 2023 · 2 mins read

About The Company

company details addi

Addi is a Colombian Buy Now - Pay Later technology company focused on credit and banking solutions. The company application allows users to apply for credit at the moment of purchase in stores with interest-free installment payments that enable borrowers to access affordable loans for their shopping.


Addi had established a functioning analytical data platform, however, they aimed to enhance its capabilities and take it to the next level by implementing a Modern Data Stack. This would be a crucial step in becoming increasingly data-driven, while also enabling them to tackle any data governance concerns or data bottlenecks in their journey to insights.

The challenge consisted of implementing a company-wide data platform that would enable facilitated self-service data access to all necessary teams while removing the data-engineering team as a technical and bureaucratic bottleneck.

The end goal was the implementation of a solid Modern Data Stack with flexible, scalable, and reliable tools that would empower data engineers and business teams to support company goals and value generation.


Mutt Data deployed an expert Data Engineering advisory and hands-on team to design and implement a Modern Data Platform, its tooling, pipelines, components, and integrations that could serve the whole company. The project applied best practices in different components of their data pipelines such as data ingestion, transformation, visualization, governance, observability, and infrastructure as code.

The project included:

  • Setting up Databricks as the place to host the company data lake with delta tables to use as a single source of truth.
  • Implementing a modern data lake house architecture with layers to separate different quality and granularities of data.
  • Selecting software engineering best practices to develop data pipelines and implement them with tools that help engineers adapt to them such as DBT for transformations, Airflow for orchestration, and Airbyte for ingestion. (Download our MDS Whitepaper for curated tool recommendations!)
  • We're AWS Advanced Partners, and this project utilized AWS tools and technology.

Mutt Data also implemented two in-house developed solutions:

  1. Archie: a pre-baked modern data stack on Kubernetes solutions with GitOps and infrastructure as code that accelerates time to value.

  2. DataOps Lib: A set of tools that create an abstraction layer on top of DBT + Great Expectation + Airflow to create transformation DAGs with data quality from SQL + YAMLs


  • The implemented Modern Data Stack increased lakehouse coverage and significantly improved both data quality and observability.
  • Hundreds of models migrated to new architecture with an accelerated new model rollout.
testimonial addi 01

Want To Dive In Deeper?

Mutt Data can help you crystallize your data strategy through the design and implementation of technical capabilities and best practices. We study your company’s business goals to understand what has to change so we can help you accomplish it through a robust technical strategy with a clear roadmap and set of milestones. Talk to one of our sales reps at or check out our sales booklet and blog.

See It To Believe It!

Explore our client results through our success stories, video testimonials, or Clutch reviews.