Senior AI Data Engineer

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