Data Engineering built for Real Estate companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Real Estate companies, this means navigating Fair Housing Act (US), RESPA while shipping fast.
Who needs Data Engineering for Real Estate?
- Disconnected listing, CRM and transaction systems
- Manual document workflows slowing closings
- Limited transparency for buyers and tenants
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Buyers and tenants now expect software-grade transparency in an industry built on paperwork and phone calls.
Real Estate founders and CTOs in trust GarudLabs with Data Engineering because we communicate like an in-house team.
Talk to our Real Estate Data Engineering specialists this week
Book a free 30-minute discovery callWhy Real Estate companies in struggle with Data Engineering
- Disconnected listing, CRM and transaction systems
- Manual document workflows slowing closings
- Limited transparency for buyers and tenants
- Integrating MLS and third-party data feeds
- Lead routing inefficiencies across agent teams
What makes our Data Engineering different for Real Estate businesses in
Data warehouse architecture (Snowflake, BigQuery)
ETL/ELT pipeline development
Data quality monitoring and alerting
BI dashboard integration
Data governance and access controls
Core Technology Stack
SnowflakeBigQueryAirflowdbtPythonKafkaAWS Glue
Timeline, investment & compliance
Typical timeline
8-16 weeks
Typical investment
$25,000 - $140,000
Data Engineering engagements in this combination typically need to account for:
- Fair Housing Act (US)
- RESPA
- GDPR (EU)
- Local real estate licensing regulations
Proven Results
"We helped a proptech platform reduce listing-to-close time by 22% with automated document workflows."
Read the full case studyLet's scope your Data Engineering project — book a free call today
Get a free project cost estimateFrequently Asked Questions
Most Data Engineering engagements take 8-16 weeks, depending on scope and how clear the requirements are upfront. We'll give you a firm timeline estimate after a short discovery call, not a generic range.
Data Engineering projects with us typically range from $25,000 - $140,000, scaled to the complexity of your requirements. We provide a detailed, itemized estimate before any work begins so there are no surprises mid-project.
For data engineering, we typically work with Snowflake, BigQuery, Airflow, dbt, chosen based on your specific scalability and integration requirements. We're not tied to a single stack and will recommend the right tools for your situation rather than our default.
A typical data engineering engagement includes data warehouse architecture (snowflake, bigquery), along with the other deliverables outlined in our proposal, such as documentation and a post-launch support window. The exact scope is tailored to your project during discovery.
Most clients come to us for data engineering because of data scattered across disconnected systems, among other related challenges. We start every engagement by mapping your specific pain points before writing a single line of code.
We've delivered multiple real estate projects addressing challenges like disconnected listing, crm and transaction systems. We helped a proptech platform reduce listing-to-close time by 22% with automated document workflows.
For real estate clients, we pay close attention to Fair Housing Act (US), RESPA, building these requirements into the architecture from day one rather than retrofitting them later. We'll confirm which specific regulations apply to your business during discovery.
The most common challenges we solve for real estate clients include disconnected listing, crm and transaction systems and manual document workflows slowing closings. We tailor our discovery process to surface the specific version of these problems your business faces.