Databricks Platform Engineer

If you're seeking a sense of community and the ability for growth, look no further. Since 1982, we have been 100% dedicated to our people. Our approach permits greater ownership for individuals and welcomes input into decisions for a thriving workplace and happy employees. Our people are the core reason for AIS' success. As an employee owned company, we are looking for individuals that are passionate about finding innovative solutions, and excited about emerging technologies and capabilities.

This role provides expert-level administrative and operational support for Databricks, including workspace setup, Unity Catalog management, secure data access, and MLOps enablement. The ideal candidate will have deep expertise in Databricks networking, Azure integrations, identity management, and Terraform automation to support scalable data science and GenAI initiatives across teams.

- Creating catalogs, connections to source systems, granting catalog access and supporting data access issues

- Manage workspace access, cluster policies, and Unity Catalog for secure data governance
- Support MLOps workflows including model training, deployment, and monitoring
- Enable data science teams with scalable compute, notebook orchestration, and pipeline automation
- Provide onboarding, documentation, and operational support for GenAI use cases

- Onboard new teams, such as the research team, to Databricks by creating workspaces, catalogs, schemas, and compute in line with EA best practices

- Provide active onboarding and orientation support to new teams and new team members to ensure minimal time to productivity within the Databricks platform

This posting is part of our ongoing talent pipeline initiative. While there may not be an immediate opening, we are actively building a network of qualified candidates for future opportunities. If you're interested in being considered when a role becomes available, we encourage you to submit your resume.

• This is a remote position with occasional travel (if needed)

• Expertise in Databricks networking and compute architecture

• Strong understanding of identity and access management within Databricks

• Proficiency in Azure networking and resource integration (Key Vault, Data Lake Storage, OpenAI)

• Advanced Terraform skills for infrastructure automation

• Experience with MLOps workflows and machine learning lifecycle management

• Familiarity with secure data governance and production data handling across workspaces

Applied Information Sciences does not discriminate on the basis of race, national origin, religion, color, gender, sexual orientation, age, disability, protected veteran status, or any other basis. Employment decisions are based solely on qualifications, merit, and business needs.