Finance Engineer — Build Revenue Models & Dashboards

AssemblyAI, Inc.; Chicago (IL); On-site; USD 160,000 - 240,000; Full time

Job summary

AssemblyAI is seeking a Finance Engineer to join the Finance team. You will build data pipelines, dashboards, and automation spanning deal desk to sales compensation to run finance with systems, not headcount.

The ideal candidate blends strong data engineering (SQL, Python, warehouse modeling) with finance fluency to model revenue, cost, and margin. You will own cross-functional analyses and ship scalable solutions that non-engineers rely on daily.

Qualifications

• Strong data engineering fundamentals across SQL, Python, warehouse modeling, and orchestration.
• Experience with financial or operational data—revenue, cost, billing, payroll, or cloud spend.
• Track record building internal tools, dashboards, or automations used daily by non-engineers.

Responsibilities

• Own unit economics — build cost-to-serve, gross margin, and contribution models by product/customer.
• Own budgeting for technology: cloud and GPU/TPU spend attribution and forecasting.
• Build and run finance dashboards — single source of truth for burn, runway, and KPIs.
• Automate budget-vs-actuals with live department views and alerts.
• Build the deal desk framework with pricing guardrails and automated quote generation.
• Automate sales compensation pipelines using CRM and billing data.
• Design and ship finance agents and internal tools for non-engineers.
• Maintain the finance data layer from billing to warehouse.
• Collaborate with VP Finance and leadership to trace discrepancies and ship fixes.

Skills

Data engineering

Measurement discipline

Full-stack mindset

Financial/operational data experience

Internal tools development

LLM-based agent workflows

Automation

Python

Communication & collaboration

Tools

dbt

Airflow

NetSuite

Stripe

Job description

AssemblyAI is seeking a Finance Engineer to join the Finance team. You will build data pipelines, dashboards, and automation spanning deal desk to sales compensation to run finance with systems, not headcount.

The ideal candidate blends strong data engineering (SQL, Python, warehouse modeling) with finance fluency to model revenue, cost, and margin. You will own cross-functional analyses and ship scalable solutions that non-engineers rely on daily.