Data Engineer

Nasze wymagania:
Python (PySpark) and strong SQL, used on large-scale datasets.
Hands-on ETL/ELT design in a lakehouse environment.
Comfort with infrastructure as code (Terraform) and DevOps work.
Solid data modeling and integration, with the discipline to keep data trustworthy.

Mile widziane:
Apache Spark and Azure Databricks. We build on Databricks, so this is a real head start — but strong distributed-processing fundamentals and the appetite to master our stack will get you there, and we'll back you while you do.
Data mesh architecture.
Other modern data platforms or ETL tools — Microsoft Fabric, Snowflake, BigQuery.
AI/ML pipelines, analytics and reporting platforms.
Data governance, security and compliance.

O projekcie:
Our products are strongest when they work as one. The Data Platform team builds the foundation under customer-facing features across the whole Medius suite. When a feature needs to know what's happening in more than one place, it comes through us.

Zakres obowiązków:
Build the pipelines behind customer features that span our products — plus the AI/ML, analytics and reporting that sit on top.
Design and maintain ETL/ELT pipelines and data processing on Azure Databricks.
Share ownership of the platform with the team: Terraform, IaC, DevOps, reliability, security, performance. Nobody owns all of it alone.
Shape our patterns and standards, and how data gets governed and kept accurate.
Help shape the backlog. Bring ideas, challenge assumptions, decide what we build next.
Spot what's missing and pick it up without waiting to be asked.

Oferujemy:
Real influence over how a young platform gets built — the patterns you set will still be here in three years.
Deep, hands-on Databricks experience on a stack that's shaping how organizations do data and AI at scale.
A clear mission: our products feel like one product because of what this team builds.
Continuous learning in a people-first culture. Curiosity is the norm here, not a perk.