Databricks Administration

Responsibilities :

Experience: 9+ years in data platform engineering, particularly focusing on Databricks/Spark environments.

9+ years in AI/LLM/Agentic platform administration (enterprise-grade).

Databricks Expertise: Strong, hands-on experience with Databricks Lakehouse architecture, Unity Catalog, Delta Live Tables (DLT), and Serverless SQL.

Technical Proficiency: Proficiency in Python, PySpark, and Spark SQL.

Cloud Platforms: Deep understanding of one or more major cloud providers (AWS, Azure, GCP) and associated services.

Own administration of Databricks accounts and multi-workspace environments across SDLC.

Define and enforce platform standards for clusters, jobs, SQL warehouses, runtimes, and workspace configurations.

Lead Unity Catalog governance strategy including catalogs, schemas, permissions, and external locations.

Design and oversee enterprise monitoring, alerting, compliance dashboards, and operational SLOs.

Lead high-severity incident management, root-cause analysis, and preventive remediation.

Establish and maintain security, audit, and regulatory compliance controls.

Drive cost governance, capacity forecasting, and performance optimization across workloads.

Define and lead Infrastructure-as-Code and automation strategy using Terraform, APIs, and CI/CD pipelines.

Standardize CI/CD, Databricks Asset Bundles, and DevOps operating models.

Partner with cloud platforms, security, and data engineering teams on architecture and governance decisions.

Own platform documentation, onboarding standards, and the operational maturity roadmap.

Coach and mentor junior and mid-level Databricks administrators and act as senior technical escalation point.

Administer Databricks accounts and workspaces across development, test, and production environments.

Configure and manage clusters, jobs, SQL warehouses, runtimes, repos, and workspace settings.

Implement monitoring, alerting, dashboards, and operational runbooks.

Provide Tier 2/3 platform support, incident resolution, and root-cause analysis.

Enforce security and governance using Unity Catalog, RBAC, service principals, and least-privilege access.

Manage secrets, audit logging, and compliance reporting.

Administer Unity Catalog objects, external locations, and cloud storage integrations.

Additional Responsibilities:

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.

Technical and Professional Requirements:

9â€11 years of experience in Databricks Administration / Big Data Platforms. Strong hands-on experience with Databricks (Workspace, Clusters, Jobs, Notebooks). Experience with Apache Spark (PySpark/Scala) and distributed data processing. Knowledge of cloud platforms (Azure preferred, AWS/GCP also acceptable). Experience with data storage systems like ADLS, S3, Blob Storage. Good understanding of data engineering concepts, ETL/ELT pipelines. Familiarity with security best practices (IAM roles, data encryption, private endpoints). Proficiency in SQL and scripting languages (Python, Shell, etc.). Experience in performance tuning and cost optimization for clusters and workloads.