Sr. Staff Platform/Data Reliability Engineer, Databricks (R5537)

Shield AI is a venture-backed defense-tech company developing intelligent systems, including autonomy software, aircraft, and simulation technologies, to protect service members and civilians. The Sr. Staff Platform/Data Reliability Engineer will make Databricks a reliable, secure, scalable, and operationally mature enterprise platform by owning observability, CI/CD standards, compute policies, deployment practices, governance, and platform enablement. The role partners with data engineering, cloud infrastructure, security, and analytics teams in regulated commercial and government environments.

Responsibilities:

• Own operational excellence for the Databricks platform, including monitoring, alerting, observability, incident response support, and production runbook patterns for data jobs and platform services
• Define and maintain CI/CD and promotion standards for Databricks assets, including workflows, jobs, notebooks, code packages, infrastructure configuration, and environment promotion from dev to prod
• Design and maintain platform standards for job orchestration, cluster and compute policies, service principal usage, environment isolation, and production execution reliability
• Establish reusable operational templates and enablement patterns for new domains onboarding to Databricks, including logging conventions, job tagging, metadata capture, and support handoff expectations
• Partner with the Senior Data Engineer to ensure ingestion and medallion patterns are implemented in a way that is observable, recoverable, cost-aware, and secure in production
• Work with the cloud/infrastructure team to align Databricks configuration and usage patterns with broader enterprise cloud standards, especially where commercial and future government-hosted environments are involved
• Help enforce technical controls for data segregation, access boundaries, and operational compliance in a highly regulated environment
• Track and improve platform health metrics such as job success rates, incident trends, data pipeline reliability, cost efficiency, and environment drift
• Document platform standards, operational expectations, and support models so the Databricks platform can scale beyond a small founding team
• Mentor internal engineers who are growing into platform responsibilities, helping expand Databricks operational knowledge within the team

Requirements:

• 12+ years of relevant experience in data platform engineering, platform operations, site reliability engineering, or modern cloud data infrastructure
• Hands-on experience with Databricks or a closely related cloud data platform in production environments
• Experience designing or operating CI/CD, environment promotion, version control, and deployment automation for data platforms and pipelines
• Strong understanding of platform operations concepts such as observability, monitoring, alerting, incident management, and reliability engineering
• Experience with compute policy design, workload isolation, service principals, and secure production execution patterns on cloud data platforms
• Ability to work effectively in a regulated or security-sensitive environment with strong expectations around access control, auditability, and operational discipline
• Strong collaboration skills and comfort partnering with cloud/infrastructure, security, data engineering, and analytics stakeholders
• Databricks certification and/or strong demonstrated expertise with Delta Lake, Unity Catalog, Workflows, and Databricks Asset Bundles
• Experience with infrastructure-as-code and platform automation in enterprise environments
• Experience supporting commercial and government or otherwise segregated environments with different compliance and access requirements
• Experience in defense, aerospace, federal, or another regulated industry