Job description

About the Company and Role HousingWire is the most trusted source for news, data, and insights in the housing market. Through its media, data, events, and performance intelligence platforms, HousingWire helps housing professionals make better decisions, faster. HousingWire Data powers one of the most extensive real estate and housing datasets across the nation, capturing high-frequency, real-time housing market activity and translating it into capabilities across the HousingWire platform – as well as powering clients to build data-driven businesses. The Senior Solutions Engineer will work with internal teams and clients to help develop the data solutions business line. Every serious deal involves a technical evaluation — match-rate tests, schema reviews, security questionnaires, licensing negotiations. Right now that work lands on AEs and data engineering. The Solutions Engineer will own this process – working closely with data and client teams to win more deals and improve the product suite and delivery systems. What you'll do Win the deal Get in front of prospects early and figure out what they actually need. Work with Sales to run evaluations and define success criteria. Know our delivery options cold (API, data share, bulk) and be direct about which one fits and which one doesn't. Work through licensing and compliance issues with finance and sales before they become deal blockers. Take care of clients When a customer signs, you don't hand them off. You see it through – credentials, schema mapping, backfill, reconciliation, the whole thing. Be the person they call when something breaks or doesn't look right. Get to the bottom of it before looping in engineering. Set clients up to move on their own—good documentation, working examples, and sandbox access so they're not waiting on us for every step. Build something that lasts Write the frameworks, templates, and tools that make the next evaluation faster and more predictable than the last one. Put together the documentation customers actually need: what the data is, where it comes from, what it doesn't cover, and how to use it. Know the competitive landscape well enough to have an honest conversation about where we win and where we don't. When we lose a deal or a customer hits a wall, make sure that signal gets back to product in a way that's specific and actionable. Who you are The right team member will have the unique ability to jump between multiple responsibilities with grace – holding a sales conversation, running a live data evaluation, getting a customer to production, and writing the process playbook to scale this business line. You're also someone clients genuinely like working with because you add value and build relationships. You'll need At least 5 years in a sales engineering or similar client-facing technical role—specifically selling data, not just software. Strong SQL and enough Python to do real work with a prospect file on the spot. Experience carrying technical deals through the full cycle—discovery to close—at six figures and above. The ability to walk into a client conversation with no warm-up and leave with their trust and a clear next step. Writing that people actually want to read. You'll produce a lot of it. Helpful but not required You've been the first or second SE at a company before. You know US real estate or mortgage data—assessor/recorder records, deeds, liens, MLS, AVMs, parcel data, foreclosure pipelines. You've worked inside Snowflake data sharing, Databricks Delta Sharing, or similar at real scale. You've sat on the customer side—at a lender, servicer, SFR shop, PropTech company, or carrier. Compensation & benefits Position level: Individual contributor. 401(k) with employer match. Comprehensive benefits including medical, dental, vision, and ancillary coverage options. Unlimited PTO plus Paid Parental Leave. Hybrid/remote work options, depending on location

Requirements

Must-haves

About the Company and Role
Win the deal
Get in front of prospects early and figure out what they actually need. Work with Sales to run evaluations and define success criteria.
Know our delivery options cold (API, data share, bulk) and be direct about which one fits and which one doesn't.
Work through licensing and compliance issues with finance and sales before they become deal blockers.
Take care of clients
When a customer signs, you don't hand them off. You see it through – credentials, schema mapping, backfill, reconciliation, the whole thing.
Be the person they call when something breaks or doesn't look right. Get to the bottom of it before looping in engineering.
Set clients up to move on their own—good documentation, working examples, and sandbox access so they're not waiting on us for every step.
Build something that lasts
Write the frameworks, templates, and tools that make the next evaluation faster and more predictable than the last one.
Put together the documentation customers actually need: what the data is, where it comes from, what it doesn't cover, and how to use it.
Know the competitive landscape well enough to have an honest conversation about where we win and where we don't.
When we lose a deal or a customer hits a wall, make sure that signal gets back to product in a way that's specific and actionable.
You're also someone clients genuinely like working with because you add value and build relationships.
At least 5 years in a sales engineering or similar client-facing technical role—specifically selling data, not just software.
Strong SQL and enough Python to do real work with a prospect file on the spot.
Experience carrying technical deals through the full cycle—discovery to close—at six figures and above.
The ability to walk into a client conversation with no warm-up and leave with their trust and a clear next step.
Writing that people actually want to read. You'll produce a lot of it.
Helpful but not required
You've been the first or second SE at a company before.
You know US real estate or mortgage data—assessor/recorder records, deeds, liens, MLS, AVMs, parcel data, foreclosure pipelines.
You've worked inside Snowflake data sharing, Databricks Delta Sharing, or similar at real scale.

Nice-to-haves

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Application prep

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Keywords to mirror

apisqlpython

Platform: bamboohr
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Parental Leave