Top Data Engineer Jobs in Malaysia

The Sr IT Engineer provides L2 support for database operations, ensuring system availability, managing incidents, and improving monitoring and reporting processes.

Design, build, and optimize data pipelines, warehouses, datamarts, and dimensional models on AWS. Develop schemas and SQL, tune queries and performance, resolve data quality issues, and provide operational support including CI/CD, monitoring, incident response, and database administration to enable data-driven decision making.

Designs and operates secure, scalable Azure infrastructure and modern data platforms. Responsibilities include landing zones, networking, identity, security, compute, infrastructure as code, monitoring, reliability, disaster recovery, data ingestion, transformation, modeling, governance, and performance optimization. The role supports mission-critical production workloads and partners with analytics, BI, security, and AI/ML teams. Required experience includes Azure infrastructure and data services, SQL, batch or streaming pipelines, cloud security, IaC, and modern analytics architectures.

Design, build, and maintain scalable ETL/ELT data pipelines and data lake/warehouse solutions using Snowflake or Databricks on Azure. Implement ingestion, transformation, data quality checks, monitoring, and performance optimization. Collaborate with Analytics, Data Science, Product, and Engineering on architecture and data consumption; contribute to governance and CI/CD practices.

The Senior Data Engineer will develop and maintain a Data Management Platform, ensuring its stability and compliance while leading a project team in delivering data solutions and optimizing processes.

Design, build, and automate ETL/data pipelines to support AI/ML workflows; integrate backend systems and APIs; ensure data governance, security, and compliance; deploy ML models to production; use SQL, Python, Spark, Hadoop, Kafka and cloud data services.

Provide L2 database operations support across incident, request, change and problem management for 24/7 coverage. Install, upgrade, patch, monitor, troubleshoot and ensure availability, backups, access controls and security compliance. Meet SLAs and metrics, develop procedures, build operational reports and dashboards, and leverage AI/agentic solutions to automate workflows and improve IT operations efficiency.

Design, build, and maintain data pipelines and Azure data warehouse infrastructure. Ensure data quality, governance, performance tuning, automation, and provide BI insights using Power BI or QlikSense.

Support APAC Claims Operations by producing and automating reports, reconciling multi-system data, resolving quality issues, and developing scalable dashboards. Build SQL queries, Python automation workflows, data validation processes, and documentation. Deliver ad hoc analysis and leadership insights while piloting AI applications such as claims classification, anomaly detection, document summarization, and natural-language querying. Partner across markets to improve reporting efficiency, data quality, and operational decision-making.

Design, build, and maintain scalable ETL and real-time data processing systems on Databricks and AWS. Develop Spark-based pipelines, ensure data quality and governance, implement security controls, automate infrastructure with Terraform, and collaborate with analysts and engineers to resolve issues and optimize performance.

Design, build, and productionize data science solutions and scalable ETL/ELT pipelines. Create self-service BI (Tableau/Power BI/Superset), ensure data integrity across BI platforms, deploy ML models using R/Python, manage CI/CD and workflow tools, and work within Agile/Scrum to prioritize and deliver data products.

Design, build, and optimize end-to-end data pipelines and cloud data platforms. Implement ETL/ELT, ensure data quality, governance, and security, collaborate with architects and stakeholders, and support analytics and AI initiatives within agile, client-facing engagements.

Build, automate, and operate enterprise-scale data platforms using Databricks, Snowflake, Microsoft Fabric, Kubernetes, and cloud technologies. Responsibilities include Infrastructure as Code, CI/CD, GitOps, platform provisioning, reliability engineering, observability, security, governance, incident remediation, performance optimization, and FinOps. The role supports multi-environment deployments and self-service capabilities for data engineering and analytics teams.

Lead Customer 360 data engineering initiatives across Customer and Sales domains. Design data integration, ingestion, curation, governance, quality, harmonization, and common data models. Build scalable cloud-based data capabilities and integration pipelines while supporting data products, use cases, and analytics. Collaborate with business owners, regional partners, and technology teams to define strategy, roadmaps, prototypes, and MVPs, serving as a subject matter expert in Customer 360 data.

Operate a 24x7 data centre network operations centre, monitoring network systems and infrastructure, troubleshooting incidents, maintaining routers, switches, firewalls, and related equipment, and performing upgrades and configuration changes. The role manages incidents, security alerts, documentation, change processes, performance optimization, hardware inventory, cabling, remote hands, and data centre operations while collaborating with technology, security, facilities, and vendor teams.

Design, build, and maintain centralized data systems, pipelines, warehouses, and lakes. Implement ETL processes, optimize data flow, produce analytics and reports, support stakeholders, ensure cross-region data security, and create tooling for product and business insights.

The Data Engineer will manage database design, ETL development, T-SQL programming, and optimize performance across SQL Server environments while supporting data integrity and migrations.

Design, operate, and optimize data pipelines and infrastructure to ensure data quality, enable analytics, and support product and engineering teams. Provide operational support, troubleshoot production issues, automate processes, improve governance, and collaborate cross-functionally to maximize data-driven business impact.

Manage the data lifecycle, drive the data platform roadmap, establish best practices in analytics, reporting, and data governance while overseeing a team of engineers and analysts.

The Site Reliability Engineer III will enhance reliability and scalability of the data platform services, manage big data tools, support on-call responses, contribute to automation, and optimize cloud infrastructure on AWS.

Design and implement data architecture and secure integration patterns to move insurance, reinsurance, and investment feeds into and out of Oracle Fusion Financials (including AHCS). Lead data migration, testing (SIT/NFT), quarterly upgrades, data governance, and collaborate with cross-functional and cross-geo teams to ensure data integrity, security, and performance for IFRS 17 and consolidation processes.

Lead design, build, and optimization of high-volume ETL/ELT and streaming pipelines, own data warehouse/datamart design and migration, partner with analytics and ML teams, maintain reliability and governance, mentor junior engineers, and evaluate AI-assisted development tools to improve productivity and pipeline quality.

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.