Role : Data & AI Ops Engineer
Location : Klang Valley, KL (project-based)
YOE : 6-10 Years
Type : Permanent
The Data & AI Ops Engineer provides end-to-end technical expertise in designing, building, and operating scalable data and AI-enabled platforms. This role ensures reliable, high-quality data pipelines, models, and integrations that support analytics, reporting, and AI-driven solutions across the organization.
The position plays a key role in data architecture, API-based integration, performance optimization, and operational support, ensuring data availability across dashboards, applications, and backend systems while meeting SLA requirements for Incident Requests (IR) and Service Requests (SR).
Job Description:
- Design, develop, and maintain scalable data pipelines and integration workflows for analytics, reporting, and operational systems
- Ensure data quality, consistency, and reliability through validation, cleansing, and transformation processes
- Collaborate with developers, business analysts, and system owners to define data requirements and deliver business-aligned solutions
- Optimize data storage and retrieval performance across databases, data lakes, and cloud platforms for batch and real-time processing
- Build, deploy, and enhance data models, APIs, and ETL/ELT frameworks in line with architecture and governance standards
- Monitor and resolve data-related IRs and SRs in accordance with SLA and operational expectations
- Support data-centric IT initiatives, including planning, coordination, risk mitigation, and stakeholder engagement
- Maintain clear documentation for data flows, schemas, and integration logic to support audit, compliance, and knowledge sharing
- Ensure seamless integration with core business systems and external platforms
- Continuously evaluate and adopt emerging data and AI technologies to improve efficiency and solution performance
Key Skills & Requirements:
- Strong understanding of data architecture, data modeling, and ETL/ELT pipeline design
- Experience with enterprise data platforms (RDBMS required; Azure Data Factory, Databricks, Power BI are a plus)
- Familiarity with API-based integration (REST, SOAP, MQ)
- Knowledge of cloud platforms (Azure, AWS, or GCP)
- Understanding of data governance, security, privacy, lineage, and compliance requirements
- Awareness of AI/ML fundamentals, including chatbot solutions, predictive analytics, and model deployment
- Experience in BI and reporting frameworks for visualization and decision support
- Strong documentation, communication, and stakeholder engagement skills
- Ability to operate in dynamic environments, troubleshoot issues, and maintain operational stability
Education & Experience:
- Bachelor's Degree in Computer Science, Information Systems, Data Analytics, or related field
- Minimum 6 years hands-on experience in data engineering or data integration
- At least 3 years designing and supporting enterprise-scale data pipelines
OR
- Diploma in a relevant discipline
- Minimum 8 years practical experience in data engineering or related domains
- At least 4 years in a senior or technical lead role supporting cross-functional data initiatives
