Senior Specialist Solutions Engineer (Infrastructure & Platform)

ReqID: FEQ427R149

Location:  London

Skills: Networking, Security, Platform, DevOps, Databricks, Cloud - AWS, GCP, Azure, Infrastructure - First preference would be GCP experience

Recruiter: Dina Hussain

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.

The Impact You Will Have

• 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

What We Look For

• 4+ years in solutions architecture, technical pre-sales, or a Network architecture 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
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
• Willingness to travel up to 30% as needed

Nice to Have

• 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 you'll position against
• Background in a data/AI company or cloud provider