Business Systems Engineer

Notion•San Francisco, CA

1d•$128,000 - $186,000•Hybrid

About The Position

Notion is seeking a Business Systems Engineer to own and improve systems that turn signed deals into correct invoices and accurate revenue reporting. The role spans the go-to-market and finance technology stack, including CRM, quoting and CPQ, billing, the data warehouse, marketing automation infrastructure, and the integrations between these systems. Salesforce is one part of the work, rather than its entirety. This is an engineering role with business ownership. The engineer will design how data and money move between Sales, Finance, Billing Ops, and Data teams, build automation to keep systems synchronized, and use AI to reduce manual work and provide timely signals to reps and operators. The role partners closely with Sales, Deal Desk, Billing Ops, Revenue Accounting, and Data Engineering. The position is based in San Francisco or New York City. The team works in the office on Mondays, Tuesdays, and Thursdays, known as Anchor Days, and seeks someone who is excited to work alongside colleagues in person on those days. The role’s goals include establishing a reliable GTM and quote-to-cash foundation; understanding critical data flows and shipping an initial high-value improvement within the first 90 days; developing AI-powered and agent-based workflows to reduce manual work; automating billing-critical workflows during the first year; and improving data integrity, reporting, and operational practices. Notion describes its compensation as competitive cash compensation, equity, and benefits. The estimated base salary range for San Francisco is $128,000–$186,000 per year; compensation depends on factors including location, scope, and candidate experience and expertise.

Requirements

Demonstrated experience in business systems engineering, GTM engineering, revenue operations, or a technical sales or marketing operations role.
Ability to own problems end to end and work effectively across functions.
Strong SQL skills and experience working with a data warehouse such as Snowflake or BigQuery.
Ability to design for clean, traceable data and protect data integrity across systems.
Experience building integrations with APIs, webhooks, event-driven services, reverse ETL, or automation platforms such as Zapier, Workato, or Tray.io.
Familiarity with finance systems and concepts such as quote-to-cash, billing, invoicing, and revenue recognition.
Ability to work effectively with Finance and Billing Ops.
Genuine curiosity about AI and experience applying it to day-to-day work through AI-assisted development, agents, or workflow automation.

Nice To Haves

Scripting experience in Python or JavaScript, or experience building serverless integrations.
Experience with an ERP such as NetSuite.
Familiarity with Salesforce administration and customization, including objects, flows, permissions, and integrations.

Responsibilities

Own and improve systems that turn signed deals into correct invoices and accurate revenue numbers.
Design how data and money move between Sales, Finance, Billing Ops, and Data teams.
Build automation that keeps CRM, CPQ, billing, finance, marketing automation, warehouse, and related systems synchronized.
Develop an understanding of critical data flows between GTM systems, finance systems, and the data warehouse, and ship an initial improvement to a high-value integration or workflow within 90 days.
Develop AI-powered and agent-based workflows that reduce manual work for reps, Deal Desk, and Billing Ops while improving the quality of signals available to users.
Automate billing-critical workflows, including upgrades and prorated refunds, early renewals, true-ups, and credit deferment, with audit trails Finance can trust.
Improve data integrity and reporting through data models, deduplication, validation rules, reconciliation, and monitoring, including infrastructure for accurate ARR, pipeline, dashboards, and forecasting.
Improve team operating practices, including access controls, change management, release practices, documentation, tool decisions, reusable tests, runbooks, code review, and AI-assisted development practices.
Partner with Sales, Deal Desk, Billing Ops, Revenue Accounting, and Data Engineering.