Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using modern data engineering tools and frameworks. Build and manage data storage solutions using cloud-based platforms such as AWS, Google Cloud, or Azure, with a focus on cost-efficiency and performance. Optimize data processing workflows for speed, reliability, and scalability across batch and real-time processing systems. Collaborate with cross-functional teams to gather requirements and translate business needs into technical data solutions. Implement data governance, quality checks, and monitoring systems to ensure data accuracy and integrity. Work with streaming technologies (e.g., Apache Kafka, Apache Flink) to support real-time data ingestion and processing. Ensure data security, compliance, and privacy standards are maintained across all data systems. Document system architectures, data models, and operational procedures for knowledge sharing and onboarding. Requirements Bachelors or Masters degree in...