D3 Growth Partners is a business that builds businesses. Specifically, we take the tactics and best practices from the most advanced companies, and apply them to smaller businesses to create an unfair advantage. While competitors still use fax machines and a notepad, we are using data warehouses, automation, and advanced marketing technology. In this role, we are looking for a head of analytics to build up the data function and help solve business problems for one of the companies we have partnered with. If that sounds interesting to you, read on. What makes this role awesome? Build Something from the Ground Up: You'll be responsible for building the data function from scratch in this role. We already have a clean foundation (all data in a warehouse & basic views set up), but you will have complete ownership of building the data function. Opportunities for Growth: The company assigned to this role is growing 300% per year - a super fast pace. With company growth comes new challenges and the opportunity for personal growth. A Leadership Team that Embraces Data: The leaders you will work with are super data literate, so you'll be working with a team that embraces data-driven decision-making. No Shortage of Challenging Problems to Solve: We have a TON of fun, challenging problems to solve with data related to conversion optimization, pricing, public data scraping and more. Business Problem-Solving Skills: You are great at distilling down the 'so what'. In addition to data wrangling, you'll be asking questions and proactively finding insights and opportunities. Advanced Level at SQL & Data Wrangling: You can write SQL in your sleep. You know how to do complex joins, window functions, and all the cool tricks. You understand how to take messy data and turn it into something useful. Data Visualization: You're familiar with the power of data visualization and how to present data in a way that end users can cut, filter, manipulate, and solve problems. Strong Data Integrity Intuition: We do our best to keep the data clean, but as we all know, no data is perfect. You know how to look at a set of tables and make sense of them. You can test your assumptions, and do gut checks on 'does this make sense'?. When we create data pipelines, you'll be the one making sure that data is transferred from one source to another properly.
