Job description

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. What You’ll Do Own warehouse transformations end to end — from raw ingestion through documented, stable tables that downstream teams and tools depend on Build and maintain curated data models for product usage, customer adoption, account health, and go-to-market reporting Set and enforce data practices: governance, access patterns, model ownership, freshness standards Debug data issues across the full stack — source systems, pipelines, warehouse models, BI dashboards — and drive root-cause fixes, not just patches Improve documentation and lineage so teams can self-serve without tribal knowledge Partner directly with stakeholders across the business to turn ambiguous questions into well-scoped data models Unblock teams on access, metric definitions, and data discoverability as part of a broader effort to reduce reliance on you as a bottleneck Required 6+ years in analytics engineering, data engineering, or similar, with real ownership of production data models Strong SQL and a track record shipping analytical models others depend on Hands-on with a modern cloud warehouse (BigQuery, Snowflake, Redshift, or similar) Experience with a transformation framework (dbt, SQLMesh, or equivalent) Scripting (Python or similar) for ingestion, validation, or automation Experience with a BI tool (Tableau, Looker, Metabase, or similar) Demonstrated judgment on data access and sensitive data handling Nice to Have Experience with data-backed AI applications — RAG pipelines, embeddings, LLM-powered internal tools (active area of investment for us) Product telemetry / event-stream data (Segment, Amplitude, Mixpanel) CRM/CS/GTM data sources (Salesforce, Gainsight, Outreach) Data catalogs, lineage tools, governance frameworks Workflow orchestration (Airflow or similar) PLG, adoption, entitlement, or customer health reporting Pay transparency $180,000 — $200,000 USD Harness in the news: Accelerating Our Mission to Bring AI to Everything After Code Goldman Sachs leads investment in software delivery startup Harness at $5.5 billion valuation How Harness runs 16 “startups within a startup” at scale | Jyoti Bansal Harness Research Shows AI Visibility Crisis Fueling Security Nightmare Harness has been named to the Inc. Power Partner list for software delivery success All qualified applicants will receive consideration for employment without regard to race, color, religion, sex or national origin. At Harness, we care about your privacy and are committed to protecting your personal data. For additional information on this topic, you can visit our privacy Portal: harness-privacy.relyance.ai Note on Fraudulent Recruiting/Offers We have become aware that there may be fraudulent recruiting attempts being made by people posing as representatives of Harness. These scams may involve fake job postings, unsolicited emails, or messages claiming to be from our recruiters or hiring managers. Please note, we do not ask for sensitive or financial information via chat, text, or social media, and any email communications will come from the domain @harness.io. Additionally, Harness will never ask for any payment, fee to be paid, or purchases to be made by a job applicant. All applicants are encouraged to apply directly to our open jobs via our website. Interviews are generally conducted via Zoom video conference unless the candidate requests other accommodations. If you believe that you have been the target of an interview/offer scam by someone posing as a representative of Harness, please do not provide any personal or financial information and contact us immediately at security@harness.io . You can also find additional information about this type of scam and report any fraudulent employment offers via the Federal Trade Commission’s website ( consumer.ftc.gov) , or you can contact your local law enforcement agency.

Requirements

Must-haves

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. What You’ll Do
Own warehouse transformations end to end — from raw ingestion through documented, stable tables that downstream teams and tools depend on
Build and maintain curated data models for product usage, customer adoption, account health, and go-to-market reporting
Set and enforce data practices: governance, access patterns, model ownership, freshness standards
Debug data issues across the full stack — source systems, pipelines, warehouse models, BI dashboards — and drive root-cause fixes, not just patches
Improve documentation and lineage so teams can self-serve without tribal knowledge
Partner directly with stakeholders across the business to turn ambiguous questions into well-scoped data models
Unblock teams on access, metric definitions, and data discoverability as part of a broader effort to reduce reliance on you as a bottleneck
6+ years in analytics engineering, data engineering, or similar, with real ownership of production data models
Strong SQL and a track record shipping analytical models others depend on
Hands-on with a modern cloud warehouse (BigQuery, Snowflake, Redshift, or similar)
Experience with a transformation framework (dbt, SQLMesh, or equivalent)

Nice-to-haves

Experience with data-backed AI applications — RAG pipelines, embeddings, LLM-powered internal tools (active area of investment for us)
Product telemetry / event-stream data (Segment, Amplitude, Mixpanel)
CRM/CS/GTM data sources (Salesforce, Gainsight, Outreach)
Data catalogs, lineage tools, governance frameworks
Workflow orchestration (Airflow or similar)
PLG, adoption, entitlement, or customer health reporting
Pay transparency $180,000 — $200,000 USD Harness in the news:
Accelerating Our Mission to Bring AI to Everything After Code
Goldman Sachs leads investment in software delivery startup Harness at $5.5 billion valuation
How Harness runs 16 “startups within a startup” at scale | Jyoti Bansal
Harness Research Shows AI Visibility Crisis Fueling Security Nightmare
Harness has been named to the Inc. Power Partner list for software delivery success

Application prep

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Keywords to mirror

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