Senior AI Data Engineer

At TechBiz Global , we are providing recruitment service to our TOP clients from our portfolio. We are currently looking for a dedicated Senior AI Data Engineer to join one of our clients' teams . If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you. Responsibilities: ▪ Design, build, and scale robust ETL/ELT pipelines optimized for AI workloads, including RAG, fine-tuning, and batch inference. ▪ Transform unstructured data sources such as PDFs, logs, and transcripts into structured and vectorized formats suitable for LLM consumption. ▪ Maintain and automate the data-to-model lifecycle, ensuring AI knowledge bases remain synchronized with changing business data. ▪ Develop and maintain real-time feature pipelines that support low-latency AI and machine learning applications. ▪ Integrate data platforms with Kafka and other event-driven systems to enable real-time processing and AI-driven responses. ▪ Manage and optimize Feature Stores to ensure consistency between model training and production environments. ▪ Implement automated data quality controls and validation processes to ensure the reliability and accuracy of AI training and inference data. ▪ Establish and maintain data lineage frameworks to provide traceability, auditability, and regulatory compliance across data workflows. ▪ Enforce data security, privacy, and governance standards, including PII protection and compliance with industry regulations. ▪ Manage data movement and synchronization across on-premises systems, cloud platforms, and data warehouses. ▪ Optimize data storage and retrieval strategies for Vector Databases to support high-performance RAG and AI search workloads. ▪ Collaborate with Data Scientists, ML Engineers, Software Engineers, and business stakeholders to deliver scalable AI data solutions. Requirements ▪ 10+ years of experience in Data Engineering or Backend Engineering with a strong focus on data platforms and pipelines. ▪ 2+ years of hands-on experience supporting AI/ML data pipelines, including data preparation for machine learning and generative AI applications. ▪ Expert-level proficiency in Python and SQL; experience with Java or Scala is an advantage. ▪ Strong experience building and maintaining real-time data streaming solutions using Apache Kafka, Flink, or Spark Streaming. ▪ Hands-on experience with modern data orchestration and transformation tools such as Airflow, dbt, and Prefect. ▪ Experience working with Vector Databases and Feature Stores to support AI and machine learning workloads. ▪ Strong knowledge of cloud-based data services on AWS, Azure, or GCP, including services such as Glue, Kinesis, Data Factory, or Dataflow. ▪ Experience deploying and managing data workloads in Kubernetes (K8s) environments. ▪ Proven experience handling sensitive data within regulated industries such as Fintech, Healthcare, or other compliance-driven environments. ▪ Strong understanding of data quality, governance, security, and privacy best practices. ▪ Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field. Equivalent practical experience will also be considered. ▪ Excellent problem-solving skills and the ability to collaborate effectively with cross-functional engineering, data, and AI teams. Originally posted on Himalayas