Data Engineer

About Tabs

Tabs is the leading AI-native revenue platform for modern finance and accounting teams. Tabs agents automate the entire contract-to-cash lifecycle, including billing, collections, revenue recognition, and reporting, helping teams eliminate manual work and accelerate cash flow. High-growth companies like Cursor and Statsig rely on Tabs to generate invoices directly from contracts, reconcile payments in real time, and automate ASC 606 compliance.

Founded in 2023, Tabs has raised over $91 million from leading venture capital firms including Lightspeed Venture Partners, General Catalyst, and Primary. The team is headquartered in New York and brings deep expertise in finance and AI technology.

About the Role

You'll be the first Data Engineer at Tabs, building the core data infrastructure that powers internal KPIs, customer insights, and AI systems. Your initial mandate is to design and implement the foundational data platform around core metrics and set the organization up for long-term analytical scalability. This role is ideal for an engineer who has built a data platform end-to-end and wants full ownership of the data stack. You'll operate in an environment that values ambiguity and focuses on driving real business impact.

Key Responsibilities

• Design and implement the first scalable data warehouse/lakehouse architecture to support KPI tracking and analytics
• Build and maintain reliable data pipelines for both batch and streaming data from application databases and third-party tools
• Collaborate with leadership to translate business metrics into concrete data models and schemas
• Define and own data modeling standards and best practices across the organization
• Implement comprehensive monitoring, data quality checks, and observability around pipelines and core tables
• Enable BI teams and data analysts through well-structured models and self-serve friendly datasets
• Document the data platform including lineage, definitions, and contracts to establish a shared source of truth for metrics

Required Experience

• 3–5+ years of professional experience as a Data Engineer, ideally in a mid-stage startup environment
• Solid programming skills in Python with production-level experience
• Strong SQL expertise and hands-on experience with data modeling for analytics purposes
• Hands-on experience with modern cloud data stack tools (Snowflake, BigQuery, Redshift, or similar)
• Familiarity with data pipeline orchestration tools and ETL frameworks
• Experience with data quality frameworks and monitoring solutions

💰 Compensation not publicly listed. Market estimate for similar roles: from $130K, varying by experience and location.