Brian Lipp

Sr. Data Engineer/Backend Dev​
Brian has worked in the Data field for many years in many hybrid roles combining Data Engineering, Backend Software Engineering, and Machine Learning.

Areas of Expertise

Technologies

  • Kinesis
  • S3
  • Lambda
  • EC2 Docker
  • Jenkins
  • Python
  • Terraform
  • Golang
  • Linux
  • REST API

Thought Leadership

MLOps Basics (Part IV)

So far in our MLOps journey, see MLOps Basics (Parts I-III), we have created ML research and ML model-building pipelines as well as saved them in serialized form. Saving models this way allows us…

Introduction to MLOps: A Guide to Getting Started (Parts I-III)

Part I: What is MLOps? MLOps (Machine Learning Operations) is the practice of combining the lessons learned from DevOps for the productionalization of machine learning. Its role is…

Setting Up Your Python Environment

If you run into issues with versioning and package management when working on multiple Python projects, don’t worry, you’re not alone. I will introduce two projects to hopefully…

Deconstructing the Lakehouse

The Lakehouse Databricks introduced the Lakehouse to describe a unique set of principles that have emerged in the industry. At its core, it is a hybrid of two…

Choosing a Data Store: A Helpful Guide

When starting a new project, it’s a good idea to evaluate your data storage needs. I’m going to shy away from the term database and instead, I’ll use…

Modern Data Engineering

Data Engineering: then and now Data Engineering is a relatively new concept, although the skills have been around for some time. If you Google around you will find…