Job Summary The Data Engineering Lead / DevOps Lead is responsible for building and operationalizing the core foundation of the Data Intelligence Platform Enablement Framework. This role will lead the implementation of governance-as-code, infrastructure-as-code, CI/CD automation, workspace configuration standards, platform monitoring, and observability capabilities to deliver a scalable, secure, and enterprise-ready data platform. The ideal candidate is a hands-on technical leader with strong Databricks, Azure, DevOps, platform engineering, and automation expertise who can establish engineering standards and enable self-service deployment capabilities. Key Responsibilities • Lead the implementation of the Data Intelligence Platform core infrastructure and enablement framework. • Design and build reusable platform services, deployment patterns, and engineering standards. • Develop scalable platform capabilities supporting analytics, data products, AI, and self-service development. • Establish repeatable engineering practices that support enterprise adoption and growth. • Design and implement governance-as-code frameworks across Databricks and Azure environments. • Automate provisioning and enforcement of security, access controls, Unity Catalog policies, data classifications, and governance standards. • Partner with Security, Architecture, and Data Governance teams to operationalize governance requirements through automation. • Ensure platform controls are consistently deployed across environments. • Lead infrastructure automation initiatives using Infrastructure-as-Code methodologies. • Develop and maintain Terraform modules and deployment frameworks for Databricks and Azure services. • Automate environment provisioning, configuration management, and platform scaling. • Standardize deployment patterns to improve consistency, reliability, and speed. • Design and implement enterprise CI/CD pipelines supporting data engineering, analytics, and platform workloads. • Establish automated deployment frameworks for code, infrastructure, notebooks, workflows, and platform configurations. • Enable version control, automated testing, release management, and deployment governance. • Improve developer productivity through automation and self-service platform capabilities. • Define workspace architecture, environment standards, and deployment strategies. • Manage workspace configuration, cluster policies, compute governance, secret management, and environment isolation. • Develop standards for development, testing, and production environments. • Ensure platform configurations align with security, governance, and operational requirements. • Implement platform-wide monitoring, observability, and operational health capabilities. • Define and manage logging, alerting, dashboards, performance monitoring, and incident response processes. • Establish proactive monitoring for platform health, usage, performance, security, and cost management. • Support Site Reliability Engineering (SRE) practices and operational excellence initiatives. • Provide technical leadership and mentorship to platform engineers, data engineers, and DevOps resources. • Establish engineering standards, deployment patterns, and operational best practices. • Lead troubleshooting of complex platform, infrastructure, and automation challenges. • Drive continuous improvement through automation, standardization, and platform innovation. Required Qualifications • Bachelor's degree in Computer Science, Information Technology, Engineering, or related field. • 8+ years of experience in Data Engineering, Platform Engineering, DevOps, or Cloud Infrastructure. • 5+ years of hands-on experience with Azure cloud technologies. • 5+ years of Databricks experience. • 3+ years of experience supporting Databricks platform deployments and administration. • Strong hands-on experience with Unity Catalog implementation and permissions management. • Strong experience with Terraform, Infrastructure-as-Code, CI/CD automation, and DevOps practices. • Strong understanding of cloud security, identity management, networking, and platform governance. • Experience implementing data governance and security models. • Experience implementing monitoring, observability, and operational support frameworks. • Proven ability to act as a Databricks SME and partner with infrastructure teams. • Proven ability to lead technical initiatives and drive engineering best practices. Preferred Qualifications • Databricks Certified Data Engineer or Databricks Platform certifications. • Microsoft Azure DevOps Engineer Expert certification. • Experience with Unity Catalog, Delta Lake, Azure Data Lake Storage, Azure Key Vault, and Azure Monitor. • Experience implementing Governance-as-Code and Policy-as-Code frameworks. • Knowledge of GitHub Actions, Azure DevOps Pipelines, Jenkins, or similar automation platforms. • Experience supporting enterprise Data Intelligence, Data Product, or AI platforms.