We are looking for a highly technical engineer responsible for optimizing and productionalizing Databricks code written by data scientists. The role involves optimizing Spark performance, data partitioning, and CI/CD setup (likely using Jenkins), as well as MLOps design. The engineer will work independently, ensuring technical delivery and progress tracking with a strong focus on execution.
Client Overview:
One of the largest financial institutions in Central and Eastern Europe. The client’s architecture is based on Azure Databricks and requires performance optimization and production readiness of ML workloads.
Key Competencies Required:
— Azure Databricks (DBX)
— Spark optimization & data partitioning
— Databricks Asset Bundles
— Designing and implementing MLOps frameworks
— Jenkins (or equivalent) for CI/CD automation
— Cluster/job tuning and performance monitoring
— Strong self-management and delivery ownership
Details:
— Number of required positions: 1
— Planned start date: Mid-December to January
— Remote / Onsite / Hybrid: Remote
— Geographical restrictions: EU-based only
— Desired seniority/profile: Senior Databricks Engineer with a strong background in Spark tuning and CI/CD automation. Must be independent, hands-on, and technically focused.
