Top Data Engineer Jobs in Malaysia

Build and own reliable batch and streaming data pipelines supporting trading, analytics, compliance, fraud detection, and AI/ML systems. Implement observability, data quality, anomaly detection, governance, data contracts, lineage, and access controls. Optimize warehouse performance and costs, develop scalable data models, resolve root-cause data issues, collaborate with business stakeholders, review code, and mentor engineers.

Lead mechanical design for data centre projects in Sydney, overseeing performance, energy efficiency, project delivery, client engagement, and mentoring junior engineers while incorporating industry innovations.

Design and build Renesas’s governed enterprise data platform using Azure Databricks, Unity Catalog, Delta Lake, and Spark. Develop scalable ELT/ETL pipelines, data models, catalogs, ingestion strategies, and medallion architectures. Implement governance, PII classification and masking, data quality, security, CI/CD, and DevOps practices. Collaborate with functional teams, support SAP and manufacturing data domains, contribute to architecture decisions, and mentor junior engineers.

Lead design, build, and maintain factory automation and connectivity solutions for semiconductor back-end production. Implement AI controllers, image AI, SCADA and remote command center capabilities. Integrate hardware (AGV/ARV/ASRS), collaborate with engineering and data science to deploy predictive quality and maintenance, convert business needs to IT specs, manage stakeholders, roadmap factory automation, and monitor project delivery.

Perform routine security site walks in data halls, storage rooms and offices to validate door/badge readers and cameras/sensors; identify and report security incidents, safety hazards, and hardware anomalies; coordinate vendors for installs and retrofits; support critical security events; maintain daily status reports, attend briefings, comply with PPE and NDAs, and assist with access control onboarding and presence in leased spaces.

Design, develop, and manage enterprise data platforms and pipelines (ETL/ELT) across the organization. Optimize Oracle SQL/PLSQL, implement Snowflake-based data warehousing, build BI data sources/models for Tableau/Power BI/OBIEE, support CI/CD deployments, schedule jobs (Control-M), and collaborate with global engineering teams on data architecture and operational support.

Design and execute tests for end-to-end data flows across MongoDB and Azure services, automate UI/API/data-layer tests, validate Power BI reports and SQL/MongoDB transformations, integrate tests into CI/CD, and collaborate with engineering and product teams to identify, document, and resolve data defects.

Develop, deploy, and maintain LLM pipelines and RAG QA/search systems; design and optimize prompts and multi-agent LLM architectures; operate multi‑GPU/cluster inference; build evaluation pipelines for model quality, bias, and hallucination; collaborate with product and CS teams to integrate conversational AI.

The Senior Site Reliability Engineer will enhance data platform reliability on AWS, automating processes and collaborating on incident response and architecture improvements for data services.

Design, implement and support real-time and batch data pipelines using Qlik Replicate. Manage Replicate environments, perform data replication across Oracle/Hadoop/DB2, troubleshoot production issues, and contribute to migration, modernization, and integration initiatives while providing L2/L3 support and collaborating with stakeholders.

Design, build, administer, and support Qlik Replicate data pipelines for near-real-time and batch replication across heterogeneous systems. Troubleshoot replication and performance issues, write complex SQL/PLSQL, perform Unix scripting, collaborate on data migrations and cloud modernization, document architectures, automate tasks, and provide Level 2/3 production support and stakeholder engagement.

Design and propose data center electrical and infrastructure solutions, support pre-sales and client engagements, perform site visits, create designs using CAD/Visio, manage multiple projects independently, and communicate technical solutions. Must be based in Balakong, travel for client meetings, and join immediately.

Design, build, and maintain scalable data pipelines and ETL processes; optimize data storage and retrieval; collaborate with data scientists and engineers to deliver reliable data products; implement data modeling, quality, and governance; mentor junior engineers and drive best practices.

Design and implement production-ready AI features and integrations (Azure OpenAI, Alibaba PAI), build RAG pipelines, MCP agents, and data pipelines for extraction, embeddings, and vector storage. Implement prompt engineering, safety guardrails, evaluation, and monitoring for AI-powered SaaS augmentation and partner experiences.

Design and build scalable cloud data platforms and ETL/ELT pipelines to enable AI/ML and manufacturing analytics. Deliver data products, dashboards, and self-service analytics while ensuring data quality, governance, security, and operational excellence. Partner with stakeholders to apply data and AI to business challenges.

Lead supplier quality analytics for outsourced foundry, assembly and test partners. Build and maintain ELT pipelines, implement data validation and governance, create real-time dashboards (Spotfire/PowerBI), perform statistical analysis to detect drifts and defects, and drive continuous improvement and corrective actions. Support weekend rotation.

Combine supplier quality engineering with data analytics to build ELT pipelines, validate data, create automated Spotfire/Power BI dashboards, perform statistical modeling to monitor and predict manufacturing variances, and drive continuous improvement with supplier and internal teams. Provides rotational weekend support.

Lead supplier quality analytics for outsourced foundry, assembly, and test subcontractors. Build ELT pipelines, data validation, automated testing, and interactive dashboards (Spotfire/PowerBI). Use statistical modeling to track, predict, and resolve manufacturing variability, support continuous improvement, and provide weekend rotational support.

As a Data Engineering Intern, you will support platform capabilities by extending the Python/Go backend for Airflow and Spark, modify applications, and follow best practices for system stability.