Lead/Senior AI Data Engineer
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Summary
Designs and maintains scalable batch and streaming data pipelines for analytics and machine learning, and builds RAG, vector search, and knowledge-base architectures for enterprise GenAI applications. Core stack: Python, SQL, PySpark, Databricks, Delta Lake, Kafka, and vector databases.
Attractive salary package! 5 days in office. Company is hiring multiple headcounts for Senior and Lead level. Please refer your friends too.
about job
- Design, build, and maintain scalable batch and streaming data pipelines to support analytics and machine learning initiatives
- Perform data transformation, cleansing, and validation using standard engineering frameworks
- Implement and operationalize knowledge bases, vector search, and Retrieval-Augmented Generation (RAG) architectures for enterprise GenAI applications
skills and requirements
- Bachelor's degree in Computer Science, Software Engineering
- Min 5 years of hands-on experience in data engineering, cloud analytics, or data platform development
- Strong expertise in Python, SQL, and distributed data processing using PySpark/Apache Spark
- Proven track record building streaming and batch data pipelines using tools such as Databricks, Delta Lake, and Kafka
- Hands-on experience developing RAG solution stacks, vector databases, and embeddings for GenAI use cases. Familiarity with enterprise data governance, CI/CD workflows, Git version control, and cloud-native observability.
- Needs to have some AI knowledge or experience
To apply online please use the 'apply' function, alternatively you may contact Stella at 96554170 (EA: 94C3609 /R1875382)