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

IEGG - AI Data Engineer (3rd Party Contract -1 Year Renewable)

Python and Kubernetes Software Engineer - Data, AI/ML & Analytics

Data & AI Ops Engineer