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Job Description
About the Opportunity
The Data Platform Engineering team is seeking an experienced Solutions Engineer (Azure & Databricks) to drive our enterprise data modernization strategy. You'll architect and deliver scalable analytics solutions on Azure Databricks, enabling advanced analytics, data science, and AI across the enterprise. This role requires an architect-level mindset with hands-on capability to design end-to-end solutions while partnering with stakeholders to translate business problems into robust technical architectures.
What You Will Do:
The Data Platform Engineering team is seeking an experienced Solutions Engineer (Azure & Databricks) to drive our enterprise data modernization strategy. You'll architect and deliver scalable analytics solutions on Azure Databricks, enabling advanced analytics, data science, and AI across the enterprise. This role requires an architect-level mindset with hands-on capability to design end-to-end solutions while partnering with stakeholders to translate business problems into robust technical architectures.
What You Will Do:
- Lead scalable analytics solution design on Azure and Databricks, creating patterns for ingestion, transformation, and serving using Delta Lake while translating business requirements into actionable architectures and roadmaps.
- Design, implement, and manage secure Databricks platforms with workspace/cluster provisioning, resource optimization using Delta Lake and Photon, and establish reusable reference architectures.
- Automate provisioning via Terraform, GitLab CI/CD, and scripting (Python, Bash, PowerShell) while building observability dashboards and operational readiness standards (monitoring, alerting, SLOs).
- Implement enterprise security policies, access controls, and compliance using Unity Catalog; design governance solutions for cataloging, lineage, access models, and data quality across domains.
- Partner with data scientists, ML engineers, and product teams to deploy analytical services, provide consultative guidance on architectural decisions, and resolve performance issues.
- Evaluate emerging Databricks capabilities, document best practices, mentor engineers, support on-call rotation, and enhance solution patterns for scalability and developer experience.