Infrastructure & Platform Senior Specialist Solutions Engineer

FEQ427R149

As an Infrastructure & Platform Specialist Solutions Engineer you will serve as a trusted technical advisor helping enterprise customers with the architecture administration and security of their Databricks deployments on their cloud of choice (AWS Azure or GCP). You combine solid technical expertise with a growing ability to connect architecture decisions to customer outcomes.

• Guide enterprise customers through the full lifecycle of Databricks on their cloud platform including platform administration from initial architectural design to production deployment
• Architect secure scalable enterprise deployments that satisfy complex cloud networking (virtual networks private connectivity) identity (cloud IAM and enterprise identity providers) and security compliance standards
• Act as a technical specialist in core areas such as cloud infrastructure infrastructure-as-code (IaC) cloud networking and identity management
• Support technical wins in competitive scenarios by demonstrating Databricks differentiation through custom-built solutions
• Collaborate with cross-functional resources (DSAs SAs FDE Partners) to contribute to solutions for complex customer needs
• Operate with growing autonomy on well-scoped engagements with guidance from senior architects on the most complex designs
• Influence product direction by providing structured feedback on customer requirements and competitive gaps

• 4 years in solutions architecture technical pre-sales or a senior hands-on technical role
• Strong expertise across the following areas:
• Security & Identity: Cloud security controls platform/network/data security encryption vulnerability management compliance and identity protocols. This includes cloud-native IAM (AWS IAM Microsoft Entra ID / Azure AD Google Cloud IAM) enterprise identity services (AWS IAM Identity Center Entra ID Google Cloud Identity) and federation standards (SCIM OAuth SAML OIDC)
• Networking & Deployments: Enterprise cloud networking (VPC/VNet design and peering dedicated interconnects such as AWS Direct Connect / Azure ExpressRoute / Google Cloud Interconnect and private connectivity such as AWS PrivateLink / Azure Private Link / GCP Private Service Connect) network routing performance optimisation and large-scale deployment management
• Platform Administration: High availability disaster recovery cluster orchestration observability and audit (e.g. Amazon CloudWatch / CloudTrail Azure Monitor Google Cloud Operations Suite) and cloud cost management
• Infrastructure Automation (InfraOps): Hands-on automation using IaC tools (e.g. Terraform plus cloud-native tooling such as AWS CloudFormation / CDK Azure Resource Manager / Bicep or Google Cloud Deployment Manager) to build maintain and scale complex cloud environments
• Strong coding proficiency in Python and PySpark/Spark: you must demonstrate live coding debugging and solution-building skills
• Solid grounding in distributed data systems architecture: scalable pipelines streaming architectures lakehouse patterns and cloud-native data platforms
• Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialisation in one area (e.g. real-time/streaming ML/AI data governance migrations)
• Ability to contribute to architecture discussions with senior technical stakeholders: whiteboarding design reviews and trade-off analysis
• Track record of driving platform adoption and consumption growth within accounts
• Contribute to Field Engineering thought leadership through customer-facing content workshops and community engagement
• Excellent communication skills: able to translate complex architectures into business value for both technical and executive audiences
• Bachelors or Masters degree in Computer Science Engineering or a quantitative discipline (or equivalent experience)
• Willingness to travel up to 30% as needed

• Databricks certifications (Data Engineer ML Platform)
• Cloud provider certifications at professional level (e.g. AWS Certified Solutions Architect Professional or AWS Certified Data Engineer; Azure Solutions Architect Expert; Google Professional Cloud Architect)
• Experience with competitive platforms (Snowflake cloud-native data services Azure Synapse BigQuery) understanding the landscape youll position against
• Background in a data/AI company or cloud provider