Job Summary This role involves designing building and optimizing enterprise-grade data platforms on Microsoft Azure. The ideal candidate will bring strong technical expertise in Azure Databricks Spark and data engineering along with the ability to lead teams mentor junior engineers and drive best practices across global cross-functional teams.
Key Responsibilities
Provide technical leadership for Azure Databricks-based data transformation initiatives
Design develop and maintain scalable data pipelines using Azure Databricks
Build and optimize ETL/ELT solutions for enterprise data platforms
Lead migration and modernization efforts from SQL Server and legacy systems to Azure
Develop and optimize data processing workflows using Apache Spark PySpark and SQL
Improve performance of Spark workloads through deep understanding of Spark architecture (drivers executors partitions stages tasks)
Work with Azure Data Lake Storage Gen2 (ADLS Gen2) and Delta Lake for reliable data storage solutions
Optimize Databricks clusters jobs and workloads for performance and cost efficiency
Implement data governance and secure access using Unity Catalog and Azure security best practices
Collaborate with architects DevOps teams and business stakeholders to deliver scalable solutions
Troubleshoot and resolve production issues related to data pipelines and platform performance
Support CI/CD pipelines and Infrastructure as Code (IaC) implementations
Mentor junior engineers and provide technical guidance and best practices
Must-Have Skills
Minimum 3 years of hands-on experience with Azure Databricks
Strong expertise in Apache Spark PySpark and SQL
Experience in building and optimizing ETL/ELT pipelines
Hands-on experience with ADLS Gen2 and Delta Lake
Strong understanding of Spark architecture and performance tuning
Experience in migration from SQL Server or other relational databases
Practical experience working in Azure cloud environments
Strong problem-solving and troubleshooting skills
Good-to-Have Skills
Experience with Unity Catalog and data governance frameworks
Exposure to Azure services such as Azure Key Vault Azure Monitor and Networking
Experience with CI/CD tools and DevOps practices
Knowledge of Infrastructure as Code (ARM Terraform etc.)
Experience working on enterprise-scale data platforms or analytics projects
Soft Skills
Strong communication skills with B2 English proficiency
Ability to work in globally distributed teams
Leadership and mentoring capabilities
Strong collaboration and stakeholder management skills
Analytical mindset with attention to detail
Domain Knowledge
Experience in enterprise data engineering and analytics environments
Understanding of large-scale data platform modernization initiatives
Exposure to consulting or client-facing environments is a plus
Familiarity with Agile/Kanban delivery models (e.g. ServiceNow-based workflows)
Location: Pune(Remote)
Required Experience:
Senior IC
Job Title: Senior Azure Databricks ExpertJob SummaryThis role involves designing building and optimizing enterprise-grade data platforms on Microsoft Azure. The ideal candidate will bring strong technical expertise in Azure Databricks Spark and data engineering along with the ability to lead teams m...
Job Title: Senior Azure Databricks Expert
Job Summary This role involves designing building and optimizing enterprise-grade data platforms on Microsoft Azure. The ideal candidate will bring strong technical expertise in Azure Databricks Spark and data engineering along with the ability to lead teams mentor junior engineers and drive best practices across global cross-functional teams.
Key Responsibilities
Provide technical leadership for Azure Databricks-based data transformation initiatives
Design develop and maintain scalable data pipelines using Azure Databricks
Build and optimize ETL/ELT solutions for enterprise data platforms
Lead migration and modernization efforts from SQL Server and legacy systems to Azure
Develop and optimize data processing workflows using Apache Spark PySpark and SQL
Improve performance of Spark workloads through deep understanding of Spark architecture (drivers executors partitions stages tasks)
Work with Azure Data Lake Storage Gen2 (ADLS Gen2) and Delta Lake for reliable data storage solutions
Optimize Databricks clusters jobs and workloads for performance and cost efficiency
Implement data governance and secure access using Unity Catalog and Azure security best practices
Collaborate with architects DevOps teams and business stakeholders to deliver scalable solutions
Troubleshoot and resolve production issues related to data pipelines and platform performance
Support CI/CD pipelines and Infrastructure as Code (IaC) implementations
Mentor junior engineers and provide technical guidance and best practices
Must-Have Skills
Minimum 3 years of hands-on experience with Azure Databricks
Strong expertise in Apache Spark PySpark and SQL
Experience in building and optimizing ETL/ELT pipelines
Hands-on experience with ADLS Gen2 and Delta Lake
Strong understanding of Spark architecture and performance tuning
Experience in migration from SQL Server or other relational databases
Practical experience working in Azure cloud environments
Strong problem-solving and troubleshooting skills
Good-to-Have Skills
Experience with Unity Catalog and data governance frameworks
Exposure to Azure services such as Azure Key Vault Azure Monitor and Networking
Experience with CI/CD tools and DevOps practices
Knowledge of Infrastructure as Code (ARM Terraform etc.)
Experience working on enterprise-scale data platforms or analytics projects
Soft Skills
Strong communication skills with B2 English proficiency
Ability to work in globally distributed teams
Leadership and mentoring capabilities
Strong collaboration and stakeholder management skills
Analytical mindset with attention to detail
Domain Knowledge
Experience in enterprise data engineering and analytics environments
Understanding of large-scale data platform modernization initiatives
Exposure to consulting or client-facing environments is a plus
Familiarity with Agile/Kanban delivery models (e.g. ServiceNow-based workflows)