Data Engineer

Summary: As a Data and AI Engineer, you will play a pivotal role in building and maintaining scalable data infrastructure and intelligent systems that drive data-driven decision-making across the organization. You will design and implement robust ETL pipelines, optimize database architectures, and ensure data quality and integrity across diverse sources. Your work will directly impact the performance, reliability, and scalability of data platforms while enabling advanced analytics and AI capabilities. By leveraging cloud-native technologies and cutting-edge machine learning techniques—including LLMs and computer vision—you will develop, deploy, and monitor intelligent models that solve complex business challenges and continuously evolve with changing data environments. Responsibilities: Design, develop, and maintain automated ETL pipelines to ingest, transform, and load data from multiple sources into data lakes and warehouses. Optimize database schemas and architectures across SQL and NoSQL systems to ensure high performance, scalability, and reliability. Implement data validation frameworks and automated testing to uphold data consistency, accuracy, and integrity. Build and manage scalable data storage and computing systems using cloud platforms such as ${cloud_platforms}. Monitor pipeline health, diagnose performance bottlenecks, and optimize queries to minimize latency and maximize efficiency. Develop, train, test, and deploy machine learning and deep learning models to address key business problems. Collaborate with data engineers to curate and prepare large-scale datasets, performing advanced feature engineering to enhance model accuracy. Integrate trained AI models into production environments via APIs and existing software systems. Research and implement state-of-the-art AI techniques, including Large Language Models (LLMs) and computer vision, to improve application capabilities. Continuously monitor deployed models for data drift and performance degradation, scheduling retraining cycles to maintain model accuracy.