Data Engineering & Architecture: Lead the development and evolution of big-data ecosystem and data lake architectures to enable data processing, storage, and retrieval, including the integration of structured data sources from enterprise transactional systems and trusted third parties and unstructured data sources, including IIoT data from manufacturing sites. Day to day responsibilities will specifically focus on the following -

Design and implement robust event-driven streaming architectures utilizing Kafka, Azure Events Hubs, and Azure IoT Edge.
Lead hands-on development and integration of streaming solutions using Databricks for real-time analytics and data processing.
Apply expertise in AI/ML (Artificial Intelligence and Machine Learning) to enhance event-driven applications and drive intelligent decision-making.
Collaborate with cross-functional teams to architect scalable and efficient solutions for streaming data processing.
Develop and execute c...