We are looking for a highly skilled Databricks Platform Engineer to design, implement, and manage a scalable, secure, and reliable Databricks environment supporting data engineering, data science, and MLOps workflows.

This position will work closely with a U.S.-based client, so strong communication skills and fluent English are required. The idóneo candidate combines deep technical expertise in Databricks with hands-on experience in cloud platforms, Infrastructure as Code, CI/CD, security, and cost optimization.

Key Responsibilities

- Design, implement, and manage the Databricks platform to support data engineering, data science, and MLOps workflows.
- Ensure the Databricks environment is scalable, reliable, secure, and optimized for performance and cost.
- Architect and manage Databricks environments across Development, Staging, and Production.
- Leverage Databricks native capabilities, including Delta Live Tables (DLT), Workflows, Unity Catalog, and other platform features.
- Apply best practices for Databricks architecture, governance, security, access control, and data management.
- Monitor Databricks compute resources and platform performance, identifying opportunities for optimization and cost reduction.
- Implement and maintain Infrastructure as Code (IaC) practices for provisioning and managing cloud and Databricks resources.
- Use GitHub for version control and support development and deployment workflows.
- Collaborate with data engineers, data scientists, MLOps teams, and other technical stakeholders to enable efficient development and deployment.
- Troubleshoot platform, infrastructure, compute, security, and performance issues.
- Evaluate Databricks features and limitations and recommend appropriate solutions based on business and technical requirements.




- Establish and maintain best practices for platform reliability, security, scalability, and operational efficiency.

Required Qualifications

- Proven hands-on experience designing, implementing, and managing Databricks platforms in enterprise environments.
- Deep understanding of Databricks architecture, features, capabilities, and limitations.
- Strong hands-on experience with Databricks native functionalities, particularly:
- Delta Live Tables (DLT)
- Databricks Workflows
- Unity Catalog
- Databricks compute and cluster management
- Experience managing Development, Staging, and Production environments and their respective deployment lifecycles.
- Strong experience with Infrastructure as Code (IaC).
- Experience with GitHub and version control best practices.
- Strong understanding of cloud infrastructure, with AWS experience strongly preferred.
- Experience with monitoring, security, governance, and access management within Databricks and cloud environments.
- Experience optimizing compute resources from both cost and performance perspectives.
- Strong troubleshooting and problem-solving skills.
- Ability to work effectively with cross-functional and distributed teams.
- Fluent English, both written and spoken, with the ability to communicate directly with a U.S.-based client and participate effectively in meetings and technical discussions.

Preferred Qualifications

- Experience supporting MLOps and machine learning workloads on Databricks.
- Experience with CI/CD pipelines and automated Databricks deployments.
- Experience with AWS services and their integration with Databricks.
- Knowledge of cloud security and governance best practices.
- Experience implementing cost-management and FinOps practices for Databricks.
- Databricks certifications are a plus.

📌 Databricks Platform Engineer (Argentina)
🏢 GyanSys
📍 Argentina