Responsibilities: Design and implement Databricks-based data architectures to meet business requirements. Develop and optimize data pipelines using PySpark, Scala, or SQL. Establish the Databricks Lakehouse architecture for batch and streaming data. Collaborate with cross-functional teams to integrate Databricks with cloud platforms (e.g., AWS, Azure, GCP). Ensure data security and compliance with best practices. Monitor and troubleshoot Databricks environments for performance and reliability. Collaborated with sales teams to support presales activities Supported presales activities, including solution design and customer discussions Stay updated on Databricks advancements and industry trends. Key Technical Skills & Responsibilities 12+ years of experience in data engineering using Databricks or Apache Spark-based platforms. Proven track record of building and optimizing ETL/ELT pipelines for batch and streaming data ingestion. Hands-on experience with Azure services such as Azure Data...