About Basis

Basis equips accountants with a team of AI agents to take on real workflows.

We have hit product-market fit, have more demand than we can meet, and just raised $34m to scale at a speed that meets this moment.

Built in New York City. Read more about Basis here.

About the Team

The Data Engineering team at Basis owns and builds the tooling that allows our agents to interact with data from outside of Basis.

We care deeply about clarity: clean abstractions, simple mental models, and clear interfaces that help our AI and product teams move fast without breaking things.

About the Role

As a Tech Lead on the Data Engineering team, you'll own the technical vision for how agents interact with data from other systems.

You'll design solid architectures, make trade-offs clear, and teach others how to think about distributed systems effectively. You'll ensure consistency across runtime, data, and schema layers so our systems scale predictably and stay understandable as we grow.

You'll lead by example through your code, design reviews, and documented decisions, making sure the platform is both powerful and elegantly simple.

What you’ll be doing:

Build and standardize our data platform

• Design data pipelines that ingest, validate, and transform accounting data into clean, reliable datasets.

• Define schemas and data contracts that balance flexibility with correctness.

• Build validation, lineage tracking, and drift detection into every pipeline.

• Create interfaces that make data discoverable, computable, and observable throughout the system.

Model the domain as a system

• Translate accounting concepts into well-structured ontologies: entities, relationships, and rules.

• Create abstractions that help AI systems reason safely about real-world constraints.

• Design for clarity: make complex workflows understandable through schema, code, and documentation.

Lead through clarity and technical excellence

• Own the architectural vision for your area and keep it consistent over time.

• Run effective design reviews that challenge assumptions and drive alignment.

• Mentor engineers on how to think about systems: from load testing to schema design to observability patterns.

• Simplify aggressively by removing unnecessary complexity and maintaining clean, stable abstractions.

📍 Location: NYC, Flatiron office. In-person team.