• Primary skills: Azure Databricks, Genie
Key Responsibilities: Solution Delivery & Leadership
• Lead end-to-end implementation of data engineering solutions on Azure Databricks, ensuring scalability, reliability, and maintainability.
• Drive technical design discussions and translate business requirements into well-structured Databricks/Genie-based solutions.
• Provide technical guidance, code reviews, and mentorship to ensure consistent engineering standards across the team. Databricks & Genie Development
• Build and optimize notebooks, jobs, and workflows leveraging Azure Databricks and Genie capabilities.
• Develop reusable components and patterns to accelerate delivery across multiple use cases.
• Troubleshoot production issues, perform root-cause analysis, and implement preventive improvements. Performance, Quality & Operations
• Optimize cluster configurations, job performance, and resource usage to balance speed and cost.
• Establish monitoring and operational practices for pipeline health, failures, and SLAs.
• Ensure data quality checks and validation steps are embedded into pipelines and workflows. Minimum Qualifications:
• 5–8 years of overall experience in data engineering / analytics engineering roles with ownership of production-grade delivery.
• Robust hands-on experience with Azure Databricks and Genie for building and managing data workflows.
• Solid experience with Databricks development and operationalization (jobs, workflows, notebooks).
• Ability to lead technical discussions, perform reviews, and guide implementation best practices.
• Education: BTECH, MTECH, MCA, MSC. Preferred Qualifications:
• Experience designing scalable data processing patterns and reusable frameworks within Databricks environments.
• Proven track record of performance tuning and cost optimization for Databricks workloads in enterprise settings.
• Experience establishing engineering standards (branching, reviews, release practices) and mentoring team members.
• Strong
📌 Azure Databricks, Genie (Pune)
🏢 Infosys
📍 Pune