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.