Senior AI Data Engineer – Enterprise Data Platforms

Required Qualifications • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field. • 10+ years of experience in Data Engineering, Data Architecture, or Data Platform Engineering. • Strong expertise in cloud platforms such as Azure, AWS, or GCP. • Deep experience with modern data ecosystems including data lakes, lakehouses, data warehouses, and streaming platforms. • Experience building and supporting AI/ML data pipelines and feature engineering workflows. • Familiarity with feature stores, model lifecycle support, and ML operationalization. • Experience designing and implementing LLM-related data pipelines. • Strong understanding of data governance, metadata management, lineage, security, and compliance frameworks. • Proficiency with SQL, Python, Spark, and modern data integration technologies. • Experience working with distributed data processing frameworks and large-scale datasets. Preferred Qualifications • Experience building data platforms that support AI agents and agentic workflows. • Knowledge of Retrieval-Augmented Generation (RAG) architectures and semantic search solutions. • Experience with vector databases, embeddings, and knowledge graph technologies. • Exposure to data mesh and domain-oriented data architecture principles. • Experience supporting enterprise AI transformation initiatives. • Familiarity with MLOps, DataOps, and platform engineering practices. • Experience working in highly regulated enterprise environments.