← Case files · Case file 02
ImmoScout24 Austria
Iterable lifecycle integration, plus search, listing and SEO work across React and Node, inside a tested distributed real-estate platform.
The problem
ImmoScout24 is one of the most-used real-estate platforms in Austria and part of the wider Scout24 group. The work sat inside a mature distributed system: search and listing flows, SEO-sensitive pages, marketing automation, and integration points that had to keep working under normal product-delivery pressure.
The existing system already had strong unit, integration, and e2e coverage. My contribution was not a rewrite — it was getting productive in that environment, making targeted changes, and matching the team's expectations for testing, review quality, and production safety.
My biggest challenge
The steepest learning curve was adapting to the quality expectations of a DAX-listed engineering organization. The codebase was tested at every layer across distributed services, with SSO federated from Scout24's German platform. Small changes still required clear reasoning, good coverage, and careful review.
I had to level up my testing discipline, communicate more precisely with senior engineers, and learn when to sync with my mentor. That calibration mattered: ask too early and you create noise; wait too long and you block delivery.
What I delivered
Iterable lifecycle integration
Integrated Iterable into the React and Node.js product flows: mapping platform data onto Iterable's data model, feeding the events lifecycle messaging depends on, and handing marketing the ability to run targeted campaigns without engineering in the loop for every change.
Search and listing flows
Shipped focused improvements across React and Node.js in search and listing, reviewed against an existing product and testing culture rather than a greenfield codebase.
SEO-sensitive delivery
Worked on technical SEO where page structure, rendering behaviour, and release quality had direct product impact. The team tracked organic visibility closely, so regressions had to be avoided.
Enricher task upgrades
Upgraded the functional-style enricher tasks that process and transform property data — improving reliability and maintainability of the data pipeline.
Business impact
- Iterable
- Lifecycle messaging integrated end to end
- React + Node
- Search and listing improvements shipped
- SEO
- Release-sensitive delivery
The impact was practical: targeted search, listing, and SEO changes shipped inside a mature production platform, while the Iterable integration reduced the engineering dependency for campaign setup. Exact commercial metrics aren't mine to disclose, so the public proof stays with the systems and delivery scope I can substantiate.
For a contract buyer, the useful signal isn't a greenfield demo. It's evidence that I can enter a mature system, respect the quality bar, and ship targeted product / integration changes without increasing release risk.
What I took away
This project reset my default expectations for test coverage and review quality. A fully tested distributed system doesn't remove the need for judgment — it gives good engineers the confidence to make smaller, better-scoped changes.
On the human side, I learned when to reach out to a mentor and when to push through on my own. That calibration — knowing when to sync and when to execute — is now a core part of how I operate in any team.