Carta is hiring a Analytics Engineer in Waterloo!
The Company You’ll Join
At Carta we create owners and make private markets liquid.
We live in a world where some people live on the equity stack and enjoy exponential wealth growth and preferential tax treatment; others live on the debt stack and may work their entire lives for a company and retire only with the cash they’ve managed to save from their paychecks. Our contribution to solving the wealth inequality problem is moving people from the debt stack (payroll) to the equity stack. By making it as easy to issue equity to employees as it is to put them on payroll, we can create more owners.
At Carta, we are helpful, transparent, fair, and kind. We are relentless executors, unconventional thinkers, and masters of our craft.
Learn more about our Series G fundraising round here.
The Team You’ll Work With
Our mission is to enable data-driven decisions and products across Carta by collecting accurate data, building scalable infrastructure and delivering advanced analytics. We believe in building a strong data foundation to ensure data quality and to promote self-service across the company. In addition, the data team works on developing proprietary data products using Carta’s rich and unique dataset. The team is split between Data Science, Machine Learning, Analytics Engineering, and Data Engineering. We like to partner with each other and with Cartans across the company to get our work done. We constantly think about how we can improve and grow.
The Problems You’ll Solve
Your responsibilities will range from identifying our core metrics to creating scalable data models and building a self-serve data platform that allows internal teams to quickly build solutions on top of the data you support. In addition, the data you will manage will be used to drive Looker dashboards and other integrations for self-service capabilities for our internal customers. You will continue to evaluate how we can use our data to help teams operationalize decision making through the various tools we have at our disposal
Examples of responsibilities include:
- Build flexible and scalable data models to simplify our complex source data
- Partner with Product & Business Data Science teams to identify, document and create cross-company core metrics
- Establish testing framework for any changes to the core models
- In partnership with Product & Business Data Science teams establish Looker training curriculum and have primary responsibility for Looker adoption
- Partner with teams throughout Carta on identifying opportunities and building solutions to help in simplifying operations while producing rich and accurate data sets for us to use
- Constantly identify opportunities for providing self-service tooling to our internal partners
The Impact You’ll Have
By building scalable self-service solutions you will enable easier and faster decision making. In addition, you will be able to increase productivity and accuracy of our data team, and operations and product teams as well
Successful candidates in this role will always look for a balance between fast delivery and building for scale. You don’t follow the status quo but look for ways to improve how we do things. You are able to talk to technical and business users and explain your work, and are able to be a good partner to your team and to your customers. Building relationships is a priority. Even though our toolstack (Airflow, DBT, Redshift & Looker) are a good start, you will always be in the know on the latest and greatest technology we could utilize. You concentrate on automation and self service. Example of problems you will solve include:
- Scaling Looker as a platform to solve operational use cases as well as increase self service adoption around the company
- Evaluating and rearchitecting our data model to support existing and future products
- Partnering with external teams to help in data modeling requirements to support analytics
- Partner with the rest of data team to develop best in class software solutions to stand up products based on our data
- Partnering with Operations team to automate some of the manual work they are doing today with data we can provide
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