AI Data Engineer -Azure

About the Company: We are a leading innovator in the technology sector, dedicated to delivering cutting-edge solutions that drive business transformation and enhance operational efficiencies. Our team is composed of creative thinkers and problem solvers who are passionate about leveraging technology to create impactful results for our clients. With a focus on cloud computing, data management, and AI-driven approaches, we are committed to fostering a culture of continuous learning and growth. About the Role: As an AI Data Engineer specializing in Azure, you will play a crucial role in designing, developing, and managing scalable and secure data pipelines. You will be responsible for architecting cloud-based data solutions, integrating both structured and unstructured data sources, and optimizing ETL workflows. This position offers the opportunity to work with advanced analytics and support BI use cases within the Azure ecosystem, contributing to the deployment of enterprise-level data warehousing solutions. Key Responsibilities: Design, develop, and manage scalable and secure data pipelines using Azure Databricks and Azure Data Factory. Architect cloud-based data solutions integrating structured and unstructured data sources. Write clean, efficient, and reusable code primarily in Python for cloud automation, data processing, and orchestration. Build and optimize ETL workflows ensuring seamless data integration across platforms. Develop data models using normalization and denormalization techniques to support OLTP and OLAP systems. Manage Azure-based storage solutions including Azure Data Lake and Blob Storage. Troubleshoot performance bottlenecks in data flows and ETL processes. Integrate advanced analytics and support BI use cases within the Azure ecosystem. Lead code reviews and ensure adherence to version control practices, such as Git. Contribute to the design and deployment of enterprise-level data warehousing solutions. Stay current with Azure cloud technologies and Python ecosystem updates to adopt best practices and emerging tools. Requirements: 4-7 years of experience in data engineering or related fields. Strong SQL skills. Expertise in Azure Databricks and hands-on experience with Apache Spark. Proficiency in Pyspark and managing Azure Blob Storage / Azure Data Lake Storage. Experience in data modeling, normalization, and denormalization techniques. Knowledge of data warehousing and BI tools integration. Familiarity with version control practices using Git. Ability to build scalable ETL pipelines and apply AI/ML frameworks. Preferred Qualifications: Understanding of OLTP and OLAP environments. Experience with Kafka and Hadoop. Familiarity with Azure Synapse Analytics and Azure DevOps for CI/CD integration. Experience in Agile delivery methodologies. Location: Bangalore, India