Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
Benefits
- Bonus
- Benefits
- Equity
- Temporary benefits package applicable after 60 days of employment
Company Overview
Company H1B Sponsorship