Azure Databricks Developer (8-12 Years)

Job Title: Azure Databricks Developer

Experience: 8- 12 Years

Employment Type: Full-time

Location: Hyderabad

Interview Type: Only In Person

We are looking for an experienced Azure Databricks Developer to join our growing data engineering team. The ideal candidate should have strong hands-on experience in Azure Databricks and Power BI , with the ability to design, develop, and optimize scalable data solutions on the Azure platform. Experience with Databricks AI offerings (Mosaic AI) will be an added advantage.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines using Azure Databricks .
• Build and maintain robust ETL/ELT workflows for large-scale data processing.
• Develop interactive dashboards and reports using Power BI .
• Integrate data from multiple sources and ensure high-quality, reliable data pipelines.
• Optimize Databricks notebooks, Spark jobs, and overall platform performance.
• Collaborate with data engineers, business analysts, and stakeholders to understand business requirements and deliver effective data solutions.
• Ensure data security, governance, and best practices across Azure environments.
• Troubleshoot production issues and provide timely resolutions.
• Participate in code reviews and contribute to continuous improvement initiatives.

Required Skills

• 8–12 years of relevant experience in Data Engineering.
• Strong hands-on experience with Azure Databricks .
• Good experience in developing data pipelines using Apache Spark (PySpark/Scala) .
• Hands-on experience with Power BI for dashboard and report development.
• Strong knowledge of SQL and data modeling concepts.
• Experience working with Azure Data Services and cloud-based data solutions.
• Good understanding of ETL/ELT processes and data warehousing concepts.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills

• Experience with Databricks AI offerings (Mosaic AI) .
• Knowledge of Azure Data Factory, Azure Synapse Analytics, or Delta Lake.
• Exposure to CI/CD pipelines and DevOps practices for data engineering.
• Understanding of machine learning or AI-enabled data platforms.