About Chalk
Chalk is building the data platform that powers the future of machine learning applications. We tear down complexity, latency, and scale barriers that have traditionally constrained ML capabilities. Our platform combines Rust-speed performance with elegant tools that developers love to use. Leading companies depend on Chalk for everything from stopping fraudulent credit card swipes, verifying identities, and maximizing clean energy capture. We've recently raised a $50 million Series A, led by Felicis.
About the role
We are hiring a Senior Data Analyst to build the trusted data foundation Chalk uses to understand and operate the business. You will create the models, metrics, and reporting systems that connect go-to-market performance, finance and billing, and product usage. This is a hands-on role partnering closely with Revenue, Finance, Product, Engineering, and company leadership.
We're in the office 5 days a week. When unavoidable conflicts come up, we’re flexible. This is not a hybrid role.
What you'll do
Build production-grade data models that unify CRM, contracts, billing, finance, and product telemetry.
Define GTM metrics across pipeline, conversion, bookings, ARR, forecast accuracy, retention, and expansion.
Create finance and billing reporting that reconciles contracts, usage, invoices, payments, credits, and the general ledger.
Define product metrics for activation, adoption, engagement, retention, and time-to-value.
Connect product usage to commercial outcomes, customer health, infrastructure cost, and gross margin.
Automate recurring reporting and replace spreadsheet-heavy workflows with reliable self-service data products.
Partner with Product and Engineering to improve instrumentation and launch new capabilities with clear success metrics.
Establish testing, documentation, lineage, and data-quality standards for business-critical datasets.
What we're looking for
4+ years of experience in analytics engineering, data engineering, business intelligence, or a related role.
Advanced SQL skills and experience building modular, tested data models with dbt or a comparable framework.
Ideally proficiency in Python
Experience working with B2B SaaS GTM data, billing or finance workflows, and product-event data.
A track record of reconciling inconsistent systems and creating trusted metric definitions.
Strong communication, attention to detail, and comfort owning ambiguous problems in a fast-moving environment.
