AI Data Engineer

We're looking for a Senior AI Data Engineer to join a leading Singapore-based enterprise undergoing one of the region's most ambitious AI transformations.

RESPONSIBILITIES:

• Design, develop, and operate scalable data ingestion, transformation, and serving solutions across cloud and hybrid data environments.
• Build and optimise batch and streaming data pipelines to support analytics, machine learning, and AI use cases.
• Develop data transformation and processing solutions using technologies such as Python, SQL, and Apache Spark.
• Integrate data from diverse sources including APIs, databases, files, and streaming platforms.
• Build and operationalise knowledge bases and Retrieval-Augmented Generation (RAG) solutions to support Generative AI and agentic AI applications.
• Develop and maintain solutions for knowledge storage, embeddings, vectorisation, and knowledge lifecycle management.
• Ensure data pipelines and AI data solutions are scalable, reliable, secure, observable, and maintainable.
• Monitor and troubleshoot production data workflows, perform incident triage and root-cause analysis, and drive continuous improvement.
• Contribute to automation, CI/CD, version control, and deployment processes across data and AI platforms.
• Collaborate with engineers, architects, product teams, business stakeholders, and source-system owners to translate requirements into effective technical solutions.
• Provide technical guidance and mentorship to engineers and delivery partners, promoting reusable components, engineering best practices, and production readiness.
• Maintain technical documentation, metadata, data lineage, operational procedures, and solution designs.
• Apply data governance, security, access control, and enterprise compliance standards throughout solution design and implementation.
• Evaluate emerging data and AI technologies and contribute to proof-of-concepts and innovative solutions.

REQUIREMENTS:

• 5+ years of experience in Data Engineering, Data Platform Engineering, Cloud Data Engineering, or a related field.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related discipline.
• Strong hands-on experience with Python and SQL.
• Experience with Apache Spark/PySpark and large-scale data processing.
• Proven experience designing, developing, and operating production-grade batch and/or streaming data pipelines.
• Experience with modern cloud data platforms and technologies such as Databricks, Kafka, Delta Lake, Microsoft Fabric, or equivalent.
• Experience working with Generative AI, Retrieval-Augmented Generation (RAG), knowledge bases, embeddings, or vector databases.
• Understanding of data ingestion, transformation, orchestration, data quality, monitoring, and observability practices.
• Experience integrating data from APIs, databases, files, and other enterprise data sources.
• Familiarity with CI/CD, Git, DevOps, and DataOps practices.
• Understanding of enterprise data architecture, data governance, security, access control, and compliance requirements.
• Experience supporting production environments, including troubleshooting, incident management, root-cause analysis, and performance optimisation.
• Strong analytical and problem-solving skills with the ability to work through complex technical challenges.
• Excellent written and verbal communication skills, with the ability to collaborate effectively across technical and non-technical stakeholders.
• Ability to work independently, lead technical discussions, and provide guidance to other engineers.
• Self-motivated, adaptable, and passionate about emerging data and AI technologies.