About Us
Rock.estate is a fast-growing startup, specialized in the remote and real-time valuation of buildings on a country-wide scale (and beyond). We combine various forms of geo-data with statistical modeling and machine learning techniques. We are committed to building a modern data stack that empowers our teams to deliver insights, automate operations, and enable data-driven innovation.
Multiple insurers and banks already use our solution to understand the value and the risks of their customer’s houses. This enables them to digitize their product offering with frictionless customer journeys without compromising on risk management.
Position Overview
We’re hiring two versatile data professionals to strengthen our data team. Whether your strength lies in building scalable data platforms, delivering sharp business insights, or conducting applied data science & R&D, we want to hear from you.
You’ll be part of a collaborative team working across the full data lifecycle—from ingestion and transformation to modeling, infrastructure, and client-facing analysis. These roles are designed to complement each other and will evolve based on your strengths and interests.
Key Responsibilities
Depending on your profile, your work could focus more on data engineering, data analytics, or applied data science. We're open to a mix:
Data Engineering / Infrastructure:
* Build and maintain robust, scalable ETL/ELT pipelines.
* Administer Linux-based systems and automate workflows.
* Develop and maintain orchestration and CI/CD pipelines.
* Contribute to platform decisions around architecture, formats, and performance.
* Monitor and improve data reliability, latency, and quality.
Analytics & Applied Data Science:
* Collaborate with analysts, business users, and clients to define data needs.
* Design, implement, test and maintain clean data models.
* Perform ad-hoc exploratory analysis and custom studies for clients.
* Support or lead experimentation, statistical analysis, or prototype ML initiatives.
Your Profile
We’re looking for T-shaped people: deep in one area (infra, analytics, data science), broad enough to collaborate across the stack.
Required:
* At least 2 years of relevant experience (relevant studies may qualify). If you’ve got quite some years under your belt, also don’t hesitate to apply.
* Strong SQL and Python (esp. data-oriented libraries like pandas, numpy, sklearn); good grasp of data workflows.
* Experience with data orchestration tools (e.g. Airflow, Prefect, Dagster).
* Comfortable working with the Linux command line, version control (e.g. Git) and CI/CD workflows.
Nice to Have:
* Experience with cloud data stacks (AWS, GCP, Azure) and data-related services.
* Familiarity with modern data warehouses, and data modeling tools.
* Experience with ad-hoc analysis, dashboards, or client-facing data work.
* Exposure to geo-data (PostGIS, GeoPandas, QGIS).
* Practical experience with web scraping, interfacing with REST APIs, and web technologies in general.
* Experience with developing ML/AI models (e.g., clustering, regression, classification, LLM).
* Experience with R&D workflows (Jupyter notebooks, experiment tracking).
* System administration, infrastructure-as-code, cloud orchestration.
What We Offer
* Join a dynamic team where FinTech, InsurTech, and PropTech collide
* Benefit from an experienced, dynamic team striving for technical excellence.
* Be part of a flat organization with room for growth and ownership
* Enjoy a flexible schedule and remote-first culture
* Opportunities for professional development in data engineering, data science and beyond.
* Receive a competitive salary & benefits package.