Databricks Administrator

Databricks Admin

• Experience: 5–9 years of overall IT experience with substantial hands-on experience administering Databricks environments in production. • Core Expertise: Proven experience in Databricks workspace and cluster administration, user and access management, job scheduling, and environment configuration. • Platform Operations: Demonstrated ability to monitor, troubleshoot, and resolve Databricks platform issues, including performance tuning and stability improvements. • Scripting & Automation: Practical experience with scripting (e.g., Bash, PowerShell, or similar) for automating Databricks administrative tasks. • Certification: Relevant Databricks certification (e.g., Databricks Administrator or equivalent) or strong demonstrable expertise in Databricks administration. Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem. Infosys provides equal employment opportunities to applicants and employees without regard to race, color, sex, gender identity; sexual orientation, religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability. • Databricks Platform Administration: Configure, manage, and maintain Databricks workspaces, clusters, pools, and jobs across environments (dev/test/prod) for 5–9 years’ scale and complexity. • Security & Governance: Implement and manage user provisioning, access control (ACLs), secret scopes, and workspace permissions in alignment with organizational security policies. • Performance & Cost Optimization: Monitor cluster performance, right-size compute, optimize autoscaling, and implement cost-control strategies and tagging standards. • Reliability & Operations: Set up and manage monitoring, alerting, and logging; troubleshoot platform issues; perform root-cause analysis and drive permanent fixes. • Automation & Tooling: Automate provisioning, configuration, and maintenance tasks using scripts and CI/CD pipelines; standardize reusable configurations and templates. • Collaboration & Support: Partner with data engineers and analytics teams to enable best practices for notebooks, jobs, and libraries; provide L2/L3 support for Databricks-related incidents. • Compliance & Standards: Enforce workspace standards, naming conventions, and lifecycle policies; support audits and documentation of platform configurations and changes. • Integration & Environment Management: Coordinate Databricks integration with other enterprise tools and services; manage upgrades, new feature rollouts, and environment migrations.