It’s a very exciting time for Reforge and for the Data Team.
Helping People do the Best Work of Their Careers
Reforge is an amazing opportunity to work on a product that has a significant impact on people’s lives. We are taking the untapped knowledge, frameworks, and practices from industry leaders and making it accessible to our customers. Our goal is to help our members do the best work of their career by unlocking insights and then helping them apply it back to their jobs right away.
We routinely here from our members that it was the best educational experience they’ve had (better than their MBA if they got one), and that it has helped them be more confident in their role and drive a big impact for their business.
$21 Million Series A Investment
We raised our Series A investment from A16Z in February. At the time, our CEO Brian Balfour wrote about:
- The history of Reforge
- Why there’s a real need for our offering
- The solution we are building
I was lucky to be one of the earliest employees that took this from a nascent concept through today. It was an incredible time to be at the company, but today’s inflection point is even more exciting. While we bootstrapped the company to eight figures of revenue, our recent fundraising round gives us the capital to invest even more aggressively.
We are the rare startup that has real revenue with generous margins and profits, yet also has raised venture capital and the ambition to continue growing 100% each year.
The Data Team at Reforge
The data team is just getting started here at Reforge. We’re looking for people who want to be a part of a small team that is growing fast and are comfortable with ambiguity and fast paced change. It’s a great opportunity for people who want to be a part of building a strong data practice at a company that sees data as invaluable in operations as well as strategic decisions.
The nature of our product is that it’s cross functional. We create content, host events, and build relationships between people through marketing, community, operations, product, design, and engineering.
We have a central data team so that every part of the org has access to all of the data to deliver an exceptional experience. Every part of the experience should be tailored to your role, your company’s business model, where you’re located, how senior you are, what you’ve done in the platform, and what your goals are today. The data team is here to make sure teams have the information they need to deliver and iterate on an exceptional experience.
The data org owns the growth model for the business. It’s our job to help bring together the metrics for the whole business to understand how we’re trending towards our goals, what is performing well, where there is opportunity to improve, and what the greatest points of leverage are. This is especially important for a cross functional product like ours where opportunities require multiple groups within the company to collaborate.
What we’re looking for
We’re looking for someone who can take ambiguous questions, run independent analyses, and then clearly communicate their findings.
- Analysts will be required to field questions from many potential sources: the leadership team, PMs, Marketers, Engineering, Design, Operations, or support. Being able to listen to the questions of teams, clarify their goals, and then come up with the right way to analyze and summarize findings is critical.
- Often times the initial question asked is not the right one or needs to be clarified and adjusted. It is not an analysts job to mindlessly give teams the answers to their questions, but to push back when necessary and be a collaborator with their teams to gain insights that will push the product experience forward and improve the business.
An analyst should be deeply quantitative but naturally curious. This person should have opinions about software experiences and be passionate about finding ways to quantify value to end users, impact to the business, areas for improvement, and insights into behavior.
- Teams may not always know the right question to ask and the best analysts have their own opinions that they pursue.
- Analysts should understand how the product works, the user psychology of end users, and how the product is different from its alternatives. The quantitative metrics that are used to measure its performance are a direct result of finding ways to express a deep understanding of the product.
- The best analysts are looking around corners to help uncover pockets of strength, quantify areas that are under-performing, and are thinking about the best ways to influence people about what’s important and should be focused on.
An analyst should be an excellent communicator, story teller, and consultant.
- We are not looking for analysts that are simply responsible for producing charts. They will need to be able to understand the motivation behind a request, suggest alternatives, and have the conviction to push back when they disagree to foster debate.
- We want analysts who are able to tell a story with the data, explain the technical elements of an analysis but communicate why it’s important.
- We want analysts to be consultative with their peers – they need to understand what will be impactful and resonate with an audience and tailor the summary accordingly.
The Tools we Use
As much as possible, we use the best of breed technology stack available today. We have roots as a profitable, bootstrapped company so we haven’t upgraded all of our tools yet but we are constantly evaluating each of the tools to ensure we’re using the best tool for the job.
Our core sources of data:
- We have a read-replica of our production database so that we can query the latest and greatest production data in real time.
- We have a data warehouse that is populated hourly by our customer data platform, Segment.
- We are able to seamlessly run queries that mix and match data between the two systems so that we can use the latest production data with an analysis that uses raw event based data or models computed in the data warehouse.
Some of the tools we use:
- We use DBT for modeling and data transformation in our data warehouse
- We use github for our DBT models and all of our code
- We use metaplane to ensure that we are the first to know of any structural changes to our schemas as well as unexpected changes or trends within our databases.
- We use iterable as our email marketing tool
- We use Segment for our event pipeline, reverse ETL tool, and to populate our data warehouse with event level information from sources of data.
- We use Airflow for any jobs that connect to external services and to create more sophisticated models and jobs that can’t be created in pure SQL.
- We use Amplitude as our behavioral analytics tool to get insights about how people are using our product, key conversion paths and funnels, and retention behavior.
- We use Metbase as our BI tool. I’ve written about examples of how we use it here and here.
How Teams are Structured
We are rapidly building our teams and how they are structured, but our strategy is a product led experience. That means that our product team is responsible for the core experience of our members. We are structuring teams in pods that own discrete elements of the experience. While every pod may vary, they will typically have:
- A product manager
- A product designer
- A Tech Lead
- Multiple software engineers
- A marketer
- A product analyst
It will be the product analysts responsibilities to:
- Be the expert on the team about data
- Empower the team to do their own reporting and answer the vast majority of their own questions
- Do deeper analyses than any other team member can do
If this is interesting to you, please apply here.