Databricks Platform Expert

Michelin Reifen; Pune District; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Michelin Reifen in Pune, India seeks a Databricks Platform Expert to manage and optimize its Databricks environment while developing Spark-based ETL pipelines. You will work across teams to ensure high availability, security, and cost-effective usage of cloud-based data platforms.

Responsibilities include administering workspaces, configuring Unity Catalog, implementing CI/CD for notebooks and Delta Live Tables, and collaborating with cloud and security teams.

Qualifications

• 4-6 years of Databricks administration or data engineering experience.
• Strong Apache Spark programming skills (PySpark preferred).
• Hands-on with Databricks Jobs, clusters, SQL warehouses, and Unity Catalog.
• Experience with Git, CI/CD, and DevOps concepts for data pipelines.
• Knowledge of Azure cloud, IAM basics, and security patterns.

Responsibilities

• Manage and administer Databricks workspaces, clusters, SQL warehouses, serverless and jobs.
• Implement Unity Catalog with catalogs, schemas, tables, and access controls.
• Optimize policies, auto-scaling, and cost for Serverless and Classic compute.
• Develop Spark-based ETL pipelines using Delta Lake and Delta Live Tables.
• Write and review Spark code (PySpark/SQL/Scala) for data transformations.
• Collaborate with cloud/network teams on connectivity and governance.

Skills

Databricks administration

Spark programming

CI/CD expertise

Cloud security

Tools

Delta Lake

Unity Catalog

Delta Live Tables

Azure Monitor

Job description

Databricks Platform Expert

MISSION : We are seeking a highly skilled Databricks expert with hands-on experience in Apache Spark programming and strong knowledge of cloud-based data engineering platforms. The ideal candidate will be responsible for managing, optimizing, and supporting our Databricks environment, ensuring high availability, security, performance, and efficient usage across teams. This role combines platform administration with practical Spark development to support data engineering and analytics workloads.

Key Responsibilities

• Manage, configure, and administer Databricks workspaces, Clusters, SQL Warehouses, Serverless, jobs, and workspace objects.
• Implement and manage Unity Catalog, including catalogs, schemas, tables, access controls, and data lineage.
• Optimize cluster policies, auto-scaling strategies, and cost management for Serverless and Classic compute.
• Serve as the SME for Databricks infrastructure, governance, and security best practices.
• Monitor workspace performance, cluster stability, logs, job reliability, and platform health.
• Implement CI/CD pipelines for notebooks, jobs, and Delta Live Tables using Git integration.
• Support user provisioning, access controls (ACLs), secrets management, and workspace SSO.
• Write efficient Spark (PySpark / SQL / Scala) code for ETL, data transformations, and pipeline optimizations.
• Assist data engineering teams with Spark job debugging, performance tuning, and code reviews.
• Build and maintain production-grade pipelines leveraging Delta Lake, Databricks Jobs, and DLT.
• Implement and manage RBAC, SCIM provisioning, AIM, service principals, and cluster access controls.
• Ensure compliance with enterprise data governance, audit, and logging requirements.
• Manage secrets Key Vault and enforce secure credential handling.
• Support audit reports, compliance reviews, and workspace security configuration.
• Monitor job failures, cluster lifecycle performance, and system events using Databricks logs and cloud-native monitoring tools (Azure Monitor).
• Create automated alerts and observability dashboards for platform usage, cost, and performance.
• Troubleshoot Databricks runtime issues, library conflicts, and Spark execution failures.
• Collaborate with cloud and network teams on VNet, peering, and private-link connectivity issues.
• Develop cost governance policies for cluster sizes, job policies, and SQL Warehouse tiers.
• Identify opportunities to reduce cost via autoscaling, spot instances (classic clusters), and job consolidation.

Required Qualifications

• 4-6 years of experience working with Databricks as an administrator or data engineer.
• Strong expertise in Apache Spark programming (PySpark preferred; SQL or Scala is a plus).
• Hands-on experience with Databricks Jobs, cluster configuration, SQL Warehouses, and Unity Catalog.
• Deep understanding of Delta Lake, ACID transactions, and lakehouse architecture.
• Experience with Git, CI/CD, and DevOps concepts for data engineering workflows.
• Knowledge of cloud platforms ( Azure).
• Familiarity with IAM, networking basics, monitoring tools, and security patterns

Michelin, the leading tire company, is dedicated to sustainably improving the mobility of goods and people by manufacturing and marketing tires and services for every type of vehicle, including airplanes, automobiles, bicycles/motorcycles, earthmovers, farm equipment and trucks. It also offers digital mobility support services and publishes travel guides, hotel and restaurant guides, maps and road atlases. Headquartered in Clermont-Ferrand, France, Michelin is present in more than 170 countries, has 111,200 employees and operates 67 production plants in 17 different countries. Michelin has a Technology Center in charge of research and development, with operations in Europe, North America and Asia. In short, whether you look at our mission, our products or our people, Michelin is a company that truly helps you to move forward... Visit our website to discover more about us www.michelin.com