Data Engineer
About The Position
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, to help 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 Lightspeed Venture Partners, General Catalyst, and Primary. The team is headquartered in New York and brings deep expertise in finance and AI. About the role You’ll be the first Data Engineer at Tabs, building the core data infrastructure that powers our internal KPIs, customer insights, and our AI systems. Your initial mandate is to design and implement the foundational data platform around our core metrics, and set us up for long-term analytical scalability. This role is ideal for an engineer who has built a data platform end to end and wants ownership of the full data stack. You’re comfortable operating in ambiguity and focused on driving real business impact.
Requirements
- 5+ years of experience as a Data Engineer, ideally in a mid-stage startup.
- Solid programming skills in Python.
- Strong SQL skills and experience designing/data modeling for analytics
- Hands-on experience with a modern cloud data stack, such as:
- Warehouses: Snowflake, BigQuery, Redshift, Databricks, etc.
- Orchestration/transformation: dbt, Airflow, Dagster, or similar.
- Ingestion: Fivetran, Stitch, custom ingestion pipelines, etc.
- Experience building and operating production-grade data pipelines (performance, reliability, cost-awareness).
- Strong understanding of data quality, testing, and monitoring practices.
- Comfort starting from a relatively greenfield environment and making pragmatic build vs. buy decisions.
Nice To Haves
- Experience supporting BI tools (Looker, Mode, Tableau, Metabase, etc) and designing semantic layers.
- Experience in B2B SaaS, especially around revenue, usage, and customer health metrics.
- Prior experience as an early data hire or working in a small or medium, fast-growing startup
Responsibilities
- Design and implement our first scalable data warehouse/lakehouse to support KPIs.
- Build and maintain reliable data pipelines (batch and/or streaming) from application databases and third-party tools.
- Work with leadership to translate business metrics into concrete data models and schemas.
- Define and own data modeling standards and best practices.
- Implement monitoring, data quality checks, and observability around pipelines and core tables.
- Enable BI and data analysts through well structured models and self-serve friendly datasets.
- Document the data platform (lineage, definitions, contracts) and help establish a shared source of truth for metrics.
Benefits
- Competitive compensation and equity
- Unlimited PTO
- Up to 100% employer covered monthly healthcare premium (medical, dental, vision)
- Lunch provided via Sharebite, plus dinner for any later in office days.
- Parental leave up to 12 weeks
- Tax free commuter and parking benefits
- Voluntary insurances (Life, Hospital, Critical Illness, Accident)
- Employee Assistance Program (Rightway)
- Free One Medical Membership
- 401k
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
