Data Engineer

Salary Competitive

Data Engineer / Backend Engineer (Data Platform & Integrations)

We’re looking for a Data Engineer / Backend Engineer to take ownership of how data flows from our data science systems into our customer-facing product.

Today, our data lives across Microsoft Azure, Databricks, microservices, and Supabase. While each part works well in isolation, the connections between them are too manual, fragile, and inefficient. Your role will be to design and build the systems that make this seamless, reliable, and scalable.

You’ll join a small, ambitious product team of 8 engineers and work closely with both backend developers and data scientists to bridge the gap between experimentation and production.

What you’ll do

Own the architecture and implementation of data pipelines between Databricks, Azure, and our application stack
Design and build robust data flows into Supabase (Postgres) for product use
Replace ad hoc scripts and manual processes with reliable, observable systems
Build and maintain microservices that expose data to the product in a clean and scalable way
Set up and manage scheduled jobs (cron, event-driven pipelines, etc.)
Collaborate with data scientists to productionize models and datasets
Improve data quality, consistency, and performance across systems
Help define best practices for how we structure and move data across the company

What we’re looking for

Strong experience with Postgres and SQL (data modeling, performance tuning, migrations)
Solid backend experience (TypeScript and/or Python)
Experience with data platforms like Databricks and cloud environments (Azure preferred)
Experience building APIs or microservices for data access
Familiarity with Supabase or similar Postgres-based platforms is a plus
Experience with scheduling, orchestration, or workflow tools (e.g. cron, Airflow, or similar)
Ability to think in systems and architecture, not just individual scripts
Comfortable taking ownership and driving technical decisions

Nice to have

Experience working closely with data science teams
Understanding of analytics pipelines, feature stores, or ML workflows
Experience improving or standardizing messy data flows in growing teams

What we offer

A high-impact role with real ownership over a critical part of our platform
A small, experienced, and fast-moving engineering team
The opportunity to shape how data flows across the entire product
A pragmatic engineering culture focused on shipping and improving

For more information or questions please contact us at ian@proprty.ai

Perks and benefits

This job comes with several perks and benefits

Near public transit

Paid holiday

Work life balance

Flexible working hours

Social gatherings

Maternity / paternity leave

See all 9 benefits

Working at
proprty.ai

See company profile

proprty.ai is building a service to help Danish property managers leverage machine learning technology to create better condition assessments and maintenance plans. The cost of maintaining the Danish property mass is growing fast, and property managers are struggling to keep up with maintenance and regulatory responsibilities. This is not only hurting the property managers, but also the people using and living in the buildings. The challenge to live up to the EU Taxonomy for Sustainable Activities, is made harder, by not having the tools nor data to make the right strategic choices when planning and executing maintenance. With our service we aim to create property condition assessment and maintenance plans faster and more accurately than what is possible today. Using machine learning algorithms trained on millions of m2 worth of data, we can provide property managers with data to make the right decisions, when it comes to spending resources on maintenance. That way they can cut costs, improve property conditions and push the property mass towards a sustainable future. We're creating an AI powered web platform, that allows property managers to create condition assessments and maintenance plans in a fraction of the time they're using today, by mixing output from our machine learning models with boots on the ground input. It's not only faster. It provides high quality data instead of subjective information. At proprty.ai we've already signed partnerships with 18% of the Danish residential property market. We have a very real problem to solve, and a strong team to do it.