Principal Analytics Engineer

Harness is the AI Software Delivery Platform company, led by technologist and entrepreneur Jyoti Bansal (founder of AppDynamics, acquired by Cisco for $3.7B). Harness has raised approximately $570M in funding and is valued at $5.5B, backed by leading investors including Goldman Sachs, Menlo Ventures, IVP, Unusual Ventures, Citi Ventures, and more. As AI accelerates code creation, the real bottleneck has shifted to everything after the code – testing, deployments, application security, reliability, compliance, and cost optimization. Harness brings AI and automation to this “outer loop,” helping teams ship software faster while maintaining security and governance throughout the entire software delivery lifecycle.

Powered by Harness AI and the Software Delivery Knowledge Graph, the Harness Platform applies deep context and intelligent automation across the software delivery lifecycle with governance and policy-driven controls embedded throughout the platform.

Over the past year, Harness powered over 185M deployments, 82M builds, 18T flag evaluations, 8M security scans, 9.1B optimized tests, 3T protected API calls, and helped manage $2.8B in cloud spend — enabling customers like United Airlines, Morningstar, and Choice Hotels to accelerate releases by up to 75%, reduce cloud costs by up to 60%, and achieve 10x DevOps efficiency.

With a global team across 26 offices and 27 countries, Harness is shaping the future of AI software delivery — and we’re looking for exceptional talent to help us move even faster.

Position Summary

We're looking for a Principal Analytics Engineer to join our data platform team. You'll sit at the intersection of raw data and the people who rely on it, building and maintaining the models, pipelines, and reporting surfaces that power decisions across the company.

This is a hands-on technical role with real stakeholder exposure. The right person is comfortable tracing a data issue from source system to dashboard, knows how to turn a vague business question into a well-scoped data model, and cares about making data trustworthy and easy to use.

What You'll Do

• Build and maintain curated data models for product usage, customer adoption, account health, and go-to-market reporting.

• Own warehouse transformations end to end, from raw ingestion through to the stable, documented tables that downstream tools and teams depend on.