Data and AI

1 week ago

Kuala Lumpur, Kuala Lumpur, Malaysia Virtej Technologies Full time

**Job Title: Data & AI Ops Engineer

Location: Kuala Lumpur, Malaysia

Employment Type: Full time - 1 year Contractual (renewable)

Experience Level: Mid to Senior Level (6+ years experience)

Budget: RM 7000 to 7500

About the Role:

We are looking for a Data & AI Ops Engineer to design, develop, and optimize scalable data pipelines and integration workflows powering analytics, reporting, and AI-driven initiatives. This role bridges data engineering, AI operations, and systems integration, ensuring that data flows seamlessly across platforms to support real-time business intelligence and decision-making.

You'll work closely with application developers, business analysts, and data scientists to build reliable, high-performance data solutions aligned with enterprise goals.

Key Responsibilities:

Design, develop, and maintain data pipelines supporting analytics, reporting, and operational systems.

Ensure data quality, consistency, and reliability through validation and transformation processes.

Collaborate with cross-functional teams to define data requirements and deliver integrated solutions.

Optimize data storage and retrieval performance across databases, data lakes, and cloud platforms.

Deploy and enhance data models, APIs, and ETL/ELT frameworks, aligned with architectural standards.

Monitor and resolve data-related incidents and service requests as per SLAs.

Document data flows, schemas, and integration logic for compliance and knowledge sharing.

Stay current with emerging data and AI technologies to improve efficiency and solution effectiveness.

Qualifications:

Bachelor's in Computer Science, Data Analytics, or related field, with 6+ years of relevant experience

OR

Diploma in a relevant field, with 8+ years of practical experience in data engineering and integration

Minimum 3–4 years in enterprise-grade data pipeline design and maintenance

Required Skills & Experience:

Proficiency in data architecture principles, data modeling, and pipeline design

Hands-on experience with RDBMS, ETL/ELT frameworks, and distributed data processing

Experience with Azure Data Factory, Databricks, Power BI (preferred)

Familiarity with API-based integrations (REST, SOAP, MQ)

Knowledge of Azure / AWS / GCP cloud environments

Understanding of data governance, privacy, and compliance

Awareness of AI/ML fundamentals, especially for chatbots and predictive analytics

Experience with business intelligence tools and reporting frameworks

Excellent communication skills for both technical and non-technical audiences

Strong documentation and collaboration skills**

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