Robert Walters Hiring! Full Time AI Data Engineer in - Ricebowl

About the client
Our client is an innovative AI product company undergoing exponential growth,with a strong focus on expanding its AI and data space.

About the Role

• Design, build, and manage scalable data ingestion, transformation, and data-serving solutions across modern hybrid cloud platforms, ensuring reliability, security, reusability, and compliance with enterprise architecture and governance standards.

• Develop, optimize, and maintain batch and real-time streaming pipelines using technologies such as Databricks and Kafka, following best engineering practices to deliver high performance, resilience, and maintainability.

• Deliver secure, trusted, and high-quality data products that support analytics, reporting, business intelligence, and machine learning initiatives.

• Lead the design, implementation, and operationalization of Knowledge Base and Retrieval-Augmented Generation (RAG) platforms to enable scalable Generative AI and agentic AI use cases across multiple business domains.

• Architect and maintain scalable data ingestion frameworks and streaming solutions, ensuring observability, reliability, and alignment with enterprise data architecture principles.

• Perform complex data transformation, enrichment, and cleansing activities using PySpark and SQL to meet business and technical requirements.

• Monitor, troubleshoot, and continuously improve data pipelines and workflows to maintain data quality, availability, and operational stability.

• Lead integration efforts for diverse data sources, including APIs, flat files, databases, and streaming platforms, while collaborating with source system owners and downstream consumers to define effective ingestion strategies and delivery schedules.

• Own production readiness and operational support for data and AI platform components, including monitoring, incident management, root cause analysis, release coordination, and continuous service improvement.

• Collaborate on the integration of data platforms and technologies including Microsoft Fabric, Databricks, Delta Lake, and related cloud ecosystem components.

• Implement and manage knowledge repositories, embedding models, vector databases, and lifecycle management processes to support advanced AI search and retrieval capabilities.

• Drive automation initiatives through the adoption of version control, CI/CD pipelines, Infrastructure as Code (IaC), and DevOps best practices.

• Ensure adherence to data governance, security, access management, compliance, and operational risk frameworks throughout the solution lifecycle, safeguarding enterprise data and AI platforms.

What We're Looking For

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline.

• 4 - 8 years of hands-on experience in Data Engineering, Data Platform Engineering, or Cloud Data Analytics, with proven ownership of enterprise-scale production pipelines and platform services.

• Demonstrated expertise in designing, developing, optimizing, and supporting production-grade batch and real-time data pipelines, including orchestration, monitoring, observability, error handling, performance tuning, and operational support.

• Strong proficiency in Python and SQL for data ingestion, transformation, validation, and analytics workloads.

• Solid experience with Apache Spark, particularly PySpark, and a strong understanding of distributed data processing and large-scale data platform architectures.

• Hands-on experience designing and implementing Knowledge Base, Vector Database, and Retrieval-Augmented Generation (RAG) solutions to support Generative AI and Agentic AI use cases.

• Proven ability to work independently, take ownership of deliverables, and drive technical solutions from concept through production.

• Strong analytical and problem-solving capabilities, with exceptional attention to detail and a continuous improvement mindset.

• Strong understanding of enterprise data architecture principles, cloud platforms, data governance, security controls, access management, and compliance requirements.

• Experience with CI/CD pipelines, DevOps practices, release management, and production support processes within modern data and AI platform environments.

• Familiarity with observability, incident management, root cause analysis, and operational excellence practices for mission-critical data and AI solutions.

• Knowledge of modern cloud data technologies such as Databricks, Microsoft Fabric, Delta Lake, Kafka, and related ecosystem tools is highly desirable.

What's Next

If you are ready to take the next step in your career journey within a supportive global team environment-where your skills are valued and developed-this opportunity awaits your application. Click APPLY or email your resume to *************

Desired Skills and Experience

#aiengineer #dataengineer #aidata #llm #dataplatform #python #dataarchitecture

Do note that we will only be in touch if your application is shortlisted.

Robert Walters (Singapore) Pte Ltd

ROC No.: 199706961E | EA Licence No.: 03C5451

EA Registration No.: R1324990 Neha Singh