Data Analytics Engineer

About Rebar
Rebar is building the operating system for commercial HVAC, Electrical, and Plumbing suppliers. As our AI-powered quoting engine scales across top suppliers in North America, measurement and evaluation become critical infrastructure.

As a Data Analytics Engineer, you will build the systems that help us understand how our AI performs in the real world — where it succeeds, where it fails, and how it impacts downstream business outcomes. You will define core product metrics, implement monitoring frameworks, and ship internal and customer-facing data products that turn raw model outputs into trusted intelligence.

This role sits at the intersection of AI evaluation, product analytics, and data-driven product development. You will be responsible both for developing new derivative data products that create value for our customers, as well as understanding how our AI systems succeed and fail in the real world, tracking those dynamics over time, and helping build derivative data products that create value for both internal teams and customers. This role is ideal for someone who enjoys building measurement systems and analytics infrastructure as much as answering business questions.

Required Qualifications

• Bachelor’s or Master's degree in Computer Science, Data Science, or other relevant field.

• Strong Python skills, SQL proficiency, and experience with Data Warehousing

• Experience working with large, real-world datasets and ambiguous problem definitions.

• Experience writing modular, testable analytics code and working in version-controlled environments.

• Ability to design meaningful metrics and evaluation frameworks for complex systems from scratch.

• Experience building data visualizations and dashboards.

• 1–3 years of experience in analytics engineering, data science, or product analytics roles working with production data systems.

• Comfortable communicating quantitative insights to both technical and non-technical stakeholders.

Responsibilities

• Help design and build data-driven product features on top of Rebar’s historical datasets.

• Define, implement, and productionize metrics to measure AI system performance over time, including automated tracking and monitoring of regressions and drift.

• Analyze model failure modes across documents, projects, customers, and time — and communicate findings clearly to ML and product teams.

• Build durable data models, dashboards, internal tools, and lightweight product features that expose metrics, trends, and confidence signals to both internal teams and customers.

Nice to Have

• Experience evaluating or monitoring ML systems in production.

• Familiarity with computer vision, NLP, or AI-driven products.

• Experience working at a startup or in a fast-moving product environment.

Compensation and Benefits

• Salary: $130-185K, dependent on experience

• Equity: Meaningful equity package, commensurate with experience

• Benefits: Comprehensive medical, dental, and vision coverage

This is a salaried, onsite role based in NYC (Flatiron).