Job Description

About Orchard

Orchard’s mission is to make home buying and selling, stress free, fair and simple. For the average American, the home purchase and sale process takes months, creates anxiety, and is filled with uncertainty and hassle. Orchard has reimagined the end-to-end experience of buying and selling, from innovative home search tools to find the perfect home to the ability to buy a new home before selling your current one. Orchard customers manage the entire experience through a personalized online dashboard, while also getting the support of best-in-class Orchard real estate agents.

Headquartered in New York City with teammates across the US, Orchard has 150+ full time employees and 600+ real estate agents. We have financing from top-tier investors including Revolution Growth, Firstmark, Accomplice, Navitas and Juxtapose, who have also backed the likes of Pinterest, AirBnb, Shopify and Sweetgreen. We're proud to have been recognized by Crain's, Inc. 5000, Glassdoor, Parity.org and Built In on their lists of best places to work.

About the Role

Orchard is looking for a Senior Analytics Engineer to help rebuild how the business gets answers from its data. We're moving from a sprawling Looker footprint to a set of certified gold-tier models, paired with a prose-based semantic layer that lets stakeholders ask questions in plain language and get trustworthy answers. Dashboards still exist for the high-visibility metrics where everyone needs to be looking at the same number. You'll build agent analysts on top of them that surface important changes to stakeholders. You’ll own that transition end to end and help set the technical direction for analytics at Orchard.

This is a full-time role that will report to the Director of Platform Product and Data. This role can either be based in our New York headquarters on a hybrid schedule (Tuesday and Wednesday), or can be fully remote in Austin or Denver.

What You’ll Do Here

• Own the big initiatives on the analytics platform roadmap from scoping through delivery, and shape where the roadmap goes next alongside the Director.
• Take new data sources from raw ingest to production gold-tier dbt models that the rest of the company can trust. Speed and quality.
• Author and maintain the prose semantic layer: markdown documenting what each model means, how metrics are defined, what historical decisions shaped the data, and where the landmines are.
• Build and tune the LLM-powered query layer on top: prompts, retrieval, evals, and the feedback loop when it gets something wrong.
• Stand up agents that monitor certified dashboards for anomalies and trend shifts, and tune them until execs trust the alerts enough to act on them.

We’d Love to Hear From You if You Have

• 4+ years in analytics engineering, data engineering, or a hybrid data role, including time owning a significant data platform or migration from end to end.
• Deep dbt and SQL fluency. Strong opinions about grain, testing, documentation, and the limits of each.
• Comfort working in Redshift or a similar warehouse at scale.
• Built something useful with LLMs against your own data and have opinions about what works. Hands-on experience with retrieval or evals is a plus.
• Clear technical writing. You can explain a metric in a paragraph an exec reads once.
• Demonstrated ability to own technical decisions in your domain and bring stakeholders along across the org. You can push back when the data won't support what people want, and they'll still come back to you.