Azure Databrick Engineer @ Infobeans

What will your role look like

• Design, develop, and optimize data solutions for risk, regulatory, and compliance projects on the Azure platform.
• Lead on-prem to cloud migration initiatives, ensuring scalability, performance, and security.
• Administer, configure, and optimize the Azure Databricks platform, including clusters and Unity Catalog repository.
• Build large-scale batch and real-time data pipelines using Azure Data Factory and other cloud-native tools.
• Integrate Azure solutions with on-prem databases, Power BI reports, and enterprise applications.
• Collaborate with architects, engineers, and stakeholders to design and deliver enterprise-grade platforms.
• Develop, test, and enhance Python-based applications and frameworks for data processing.
• Partner with data scientists to operationalize ML models and enable streaming data use cases.
• Support production deployments, weekend maintenance, and troubleshooting of complex systems.
• Own projects end-to-end, ensuring outcomes meet business needs and adhere to data quality standards.

Why you will love this role

• Opportunity to work on cutting-edge Azure cloud and data technologies, driving transformation for regulatory and compliance solutions.
• Be part of a collaborative, dynamic team that values innovation, automation, and cloud-first thinking.
• Hands-on involvement with Databricks, real-time streaming, and big data frameworks in enterprise-scale projects.
• A culture that encourages continuous learning, ownership, and cross-functional collaboration.
• Competitive package and the chance to contribute directly to scalable, high-impact data platforms.

We would like you to bring along

• 5+ years of professional experience in Azure Cloud development and data engineering.
• Strong expertise with Azure Databricks, Azure Data Factory, Azure Functions, and Azure Data Lake.
• Proficiency in Python and SQL (T-SQL, PL/SQL, stored procedures).
• Experience building and managing batch and real-time pipelines in Azure.
• Solid understanding of CI/CD pipelines using Azure DevOps and version control systems like Git/GitLab.
• Ability to integrate diverse data sources while ensuring data quality, accessibility, and compliance.
• Strong problem-solving and debugging skills with experience in production support and optimization.
• Excellent communication and interpersonal skills, with the ability to collaborate across teams.

Good-to-have skills

• Knowledge of R programming for data processing and analytics.
• Experience enabling streaming data use-cases with Azure Event Grid, Service Bus, or Kafka.
• Familiarity with monitoring and logging tools (Azure Monitor, Log Analytics).
• Prior experience with migrating data science models to multi-node Databricks compute.
• Exposure to Oracle, SQL Server, and Data Warehouse design.
• Understanding of big data design patterns and cloud-native security practices.