We are looking for an experienced DevOps Engineer to set up, configure, and operationalize a new Databricks environment focused on business intelligence (BI), analytics, and data engineering workflows.

Working closely with an ML Ops Engineer, you will ensure the Databricks platform supports both traditional BI/data processing use cases and AI workloads. This includes secure access for data analysts, seamless integration with downstream AI/BI tools, and optimized data pipelines.

On Call Duty

Enterprise BI Solutions & Operations - Regular DevOps Engineer

Your responsibilities

• Deploy and configure Databricks workspaces for multi-team usage.
• Set up resource management policies for shared clusters, automated job clusters, and interactive analytical clusters.
• Configure role-based access controls aligned with data governance standards.
• Establish secure connectivity to on-premise and cloud data sources (SQL Server, data lake, APIs, etc.).
• Build shared data ingestion pipelines for BI and analytics teams.
• Automate daily and weekly data refresh schedules.
• Integrate Databricks with BI platforms (e.g., Power BI).
• Configure and optimize JDBC/ODBC connectors to ensure performance and reliability.
• Implement monitoring and logging for Databricks jobs and pipelines.
• Define backup and disaster recovery processes for key data sets.
• Apply cost tracking, budgeting, and optimization practices for cluster usage.
• Set up CI/CD pipelines for data engineering code and deployments.
• Manage deployment workflows for notebooks, SQL queries, and data models.
• Work with ML Ops Engineers to maintain shared infrastructure (storage, Delta Lake tables) supporting both BI and ML use cases.
• Partner with Data Engineers to maintain central data sources in Databricks.
• Collaborate with security teams to implement access controls for sensitive data.
• Enforce data governance (GDPR and internal compliance) including workspace auditing and logging.
• Document procedures for configuration, usage, and operations for all teams.
• 3+ years of experience in DevOps or Data Platform operations with cloud technologies.
• Hands-on experience with Databricks environment administration.
• Proficiency in Python (automation, scripting).
• Familiarity with BI/analytics tool integration via Databricks connectors.
• Solid knowledge of SQL and data engineering fundamentals.
• Experience with orchestration tools such as Databricks Workflows, Airflow, or Azure Data Factory.
• Understanding of Identity & Access Management in cloud environments.

Our requirements

• 3+ years of experience in DevOps or Data Platform operations with cloud technologies.
• Hands-on experience with Databricks environment administration.
• Proficiency in Python (automation, scripting).
• Familiarity with BI/analytics tool integration via Databricks connectors.
• Solid knowledge of SQL and data engineering fundamentals.
• Experience with orchestration tools (Databricks Workflows, Airflow, Azure Data Factory).
• Understanding of Identity & Access Management in cloud environments.
• Terraform
• Python (for automation)
• English level B2