ABOUT TRUEBILL 🔮
Truebill is a YC-backed startup with offices in San Francisco and Washington, D.C. Our DC office is right on the Silver Spring metro! Hundreds of thousands of people use Truebill to manage their daily finances and take control of their money. We just recently announced our $45 million Series D round of funding and are now looking to scale our all star team!
With a mission to improve the financial health of everyday people, Truebill is transforming the way people manage their expenses and grow their net worth. Through helping people cancel unnecessary subscriptions, negotiating bills, and securing refunds, we save our members money while helping them regain control over their finances.
Truebill has recently entered its next phase of growth - maturing as an organization and asking deeper questions of its user data. The data team at Truebill has tripled in the past 9 months and is continuing to push the limits of our data stack, succeeding but perhaps not in the most scalable or efficient ways. We're looking to add someone to the team who can help guide us through the architectural decisions ahead and be a builder of the next iteration of the Truebill data stack.
ABOUT THE ROLE 🤹
In this role, you will:
- Own Truebill's data warehouse end to end. You will be responsible for the architecture, evolution, and day-to-day operations. The warehouse currently includes syncing with Postgres, dbt pipelines, many external data sources, and dashboarding technology
- Create and own data freshness and quality alerting on our production data stack
- Own the framework for the creation and consumption of streaming data and the routing of that data to analytics, production, and third party systems
- Own the syncing of high volume tables and their aggregate views across
- Continue to bring best practices for scale to the data org while operating from a privacy and security first mindset
- Develop a fundamental understanding of our business and help build and grow data models that serve our operational reality
- Work daily with analytics engineering, machine learning, and engineering to operate and scale our production data stack
ABOUT YOU 🦄
- You have spent the last few years operating and building a data stack inside a hyper-growth organization with high data rates and consumer usage
- Desire to have ownership over a data warehouse both in terms of quality and performance
- You approach data engineering from a practical point of view: be a key stakeholder in buy vs. build decisions through the lens of today and our future state
- You are able to balance priorities between operational and investment in a growing data company
- You have strong opinions and a playbook for handling PII and moving data between the production and analytics environment in a safe and obfuscated way
- Experience with features stores and supporting ML and data science teams building version data sets with traceable lineage
- You understand the power of documentation and data versioning and establish best practices for the organization
- Experience with AWS, GCP, BigQuery, Terraform, Fivetran, dbt is highly desired
- You have experience with Python and Typescript and are comfortable operating at the interface between production systems and third parties
Truebill
