Conveyor is a brand new startup that has thousands of users, millions of rows of data, the nugget of a comprehensive dbt project (as of this writing, 104 models, 93 tests, 335 installed macros, 2 seed files, and 59 different source tables), and no Analytics Team. The Analytics Lead position at Conveyor is a unique opportunity to take on a large and valuable data project with little entrenched analytics overhead or debt and to influence and decide on the future direction for how data will drive business and product decisions moving forward.
Recently spun out from Aptible, Conveyor is a product-led startup with strong network effects, with some users inviting hundreds of additional companies to join them on the Conveyor platform. We need to build an analytics team to help us measure and understand product usage, network effects, marketing and sales effectiveness, and of course SaaS metrics and growth.
With our current traction and as we gear up for an upcoming fundraising milestone, we need our Analytics Lead --our first data/analytics hire--to be an analytics engineer in the truest sense of the title, and we are looking to give this new hire the responsibility and opportunity to lead the full stack of our data and analytics efforts including hiring additional analytics engineers, data engineers, and analysts as we raise funding and grow the team
As a team member responsible for helping to bridge the gap between business and technology, the Analytics Lead role requires equal amounts of business acumen and technical acumen.
- Manage and extend our existing data warehouse, ETL processes, dbt transformations to produce business valuable insights
- Use data warehouse and visualization tools (ideally Looker) to provide analyses that help stakeholders (from employees to investors) understand our business
- Work closely with product and engineering to determine product analyses requirements (i.e. event tracking or data to collect for analyses) and deliver useful, impactful dashboards and insights
- Work closely with revops to build analyses that drive GTM (ex. when should sales reach out to a new signup?) and wherever possible, operationalize them (via reverse ETL tools or alerting/notifications)
- As we grow, hire and build out the data & analytics team responsible for driving insights and analysis into Conveyor’s product-led growth and network
You might be a fit if you have:
- Ability to thrive in a fully remote organization
- Comfort working in a highly agile, intensely iterative environment
- Self-motivated and self-managing, with task organizational skills
- 4+ years of full-time work experience as an Analytics Engineer, Data Analyst, Data Engineer or similar
- Comfortable working with dbt, dbt cloud, the command line: you make good use of dbt_utils to streamline your SQL
- Significant experience with using SQL (particularly Postgres): CTEs and window functions are your jam
- Good experience with visualization tools (we use Looker) to drive product and business decisions, ideally in a product-led B2B SaaS company
- Comfort with ETL tools (we use Stitch)
- Demonstrated ability to communicate clearly and deliver value cross-functionally, and to focus on and prioritize the most important business valuable analyses
- Must be in a continental US time zone
Nice to have:
- Experience with reverse ETL tools like Census or other ways of pushing transformed, analyzed data into business/operational tools
- Understanding of B2B SaaS, PLG, fast growing startups,, and common data models/concepts (SFDC objects, SaaS Metrics, retention analysis etc.)
- Experience with using d3 (or other data tools) to visualize and analyze networks and network effects
- Experience growing a data team
- Experience scaling a data project (i.e. collaboration among multiple analysts and with other teams, quality control, testing, documentation, and migrating from Postgres to, for example, Snowflake, etc.)
Also, we know it’s tough, but please try to avoid the confidence gap. You don’t have to match all the listed requirements exactly to be considered for this role.