Specialist Solutions Architect - Azure Cloud Platform & Infrastructure
Job ID: FEQ127R316 | Remote role
About the role
As an Infrastructure & Platform Specialist Solutions Architect (SSA), you will guide customers in the administration and security of their Databricks deployments. In this customer-facing role, you will work with and support Solution Architects, requiring hands-on production experience with Microsoft Azure. SSAs help customers design and successfully implement essential workloads while aligning their technical roadmap to expand the use of the Databricks Platform.
As a deep go-to expert reporting to the Specialist Field Engineering Manager, you will strengthen your technical skills through mentorship, learning, and internal training programs, and establish yourself in an area of specialty—whether that be cloud deployments, security, networking, or more.
Responsibilities
- Provide technical leadership to guide strategic customers in the successful administration of Databricks, from design to deployment.
- Architect production-level deployments, including meeting security and networking requirements.
- Become a technical expert in an area such as cloud platforms, automation, security, networking, or identity management.
- Assist Solution Architects with advanced aspects of the technical sales process, including custom proof-of-concept content and architectures.
- Provide tutorials and training to improve community adoption (e.g., hackathons, conference presentations).
- Contribute to the Databricks Community.
Requirements
- 5+ years of experience in a technical role with deep expertise in Microsoft Azure platform architecture, including cloud security, networking best practices, and designing data platforms on cloud infrastructure.
- Deep specialized expertise in at least one of the following core domains:
- Security & Identity: Platform, network, data, and GenAI/model security, encryption, vulnerability management, compliance, and identity management (Provisioning, SCIM, OAuth, SAML, Federation).
- Networking & Deployments: Architecture design, implementation, performance optimization, and managing complex, enterprise-scale cloud deployments.
- Platform Administration: High availability, disaster recovery, cluster management, observability (logging, monitoring, audit), and cost management.
- Infrastructure Automation (InfraOps): Hands-on deployment using IaC tools like Terraform to maintain and extend complex environments (including Databricks) as technical needs evolve.
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical work experience.
- 2+ years of professional experience with big data technologies (e.g., Spark, Hadoop, Kafka) and distributed architectures.
- Hands-on experience with Python, Java, or Scala, and proficiency in SQL.
- 2+ years of experience in a pre-sales or post-sales technical role.
- Ability to meet expectations for technical training and role-specific outcomes within 6 months of hire.
- Willingness to travel up to 30% as needed.
Pay
Databricks is committed to fair and equitable compensation practices. The pay range for this role is $180,000—$247,500 USD (local pay range). Actual compensation is based on factors such as job-related skills, depth of experience, relevant certifications, and work location. The total compensation package may also include eligibility for annual performance bonus, equity, and benefits.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide—including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500—rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe, and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, and MLflow.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all employees. For specific details on the benefits offered in your region, visit our benefits page.