Lyft Engineering

MARCH 27, 2023

We’ll explore why Lyft needed a custom performance testing framework that worked in production, how we built a cross-functional solution, and how we’ve continued to improve this testing platform since its launch in 2016. We initially looked to open source and industry standard tools to help us solve these scaling issues.

Coding 131

Coding Database Systems Engineering 131

Monte Carlo

JULY 28, 2022

It could be a bad JOIN statement, an untriggered Airflow job, or even just someone at a third-party provider who didn’t feel like hitting the send button that day. The technological reason for upstream data quality challenges can be traced back to the tight coupling between data being emitted from production services and other data systems.

Pipeline-centric 52

Pipeline-centric Software Engineer Software Engineering Database-centric 52

Monte Carlo

JANUARY 12, 2023

Our modern data platform architecture story at Freshly started almost four years ago. Our modern data platform architecture story at Freshly started almost four years ago. Our first step was to create a base foundation and integrated set of capabilities from which our team could quickly deliver valuable data products.

Architecture 52

Architecture Building Data Warehouse BI 52

Towards Data Science

OCTOBER 7, 2023

Here are 5 popular applications data teams at OpenAI, Vimeo, and other companies are putting into practice today. We dug deep into the early adopters’ strategies to learn how companies are putting this technology to use today — and what it takes for a data team to implement gen-AI at scale. Getting started with LLMs?

Unstructured Data 76

Unstructured Data Finance SQL Media 76