Top Data Engineer Jobs in Kuala Lumpur

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.

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.

Provide day-to-day operational support for Back End (BE) Operations and ATO governance, maintain and enhance governance databases, produce reports and dashboards, perform data analysis, coordinate cross-site stakeholders, execute improvement actions, and support process consistency and continuous improvement across BE sites.

Support and optimize large-scale Spark/YARN jobs and storage (S3/EMR). Build job-profiling, cost-analysis, AI-assisted automation, monitoring/alerting (Prometheus, Flink/Spark), and internal ops tooling to improve stability and reduce costs.

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, 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.

Own and operate the cloud data platform, maintain IaC, optimize warehouse cost/performance, build and maintain batch and real-time ingestion and transformation pipelines, operate BI platform, and design AI-powered applications and agents (RAG/LLM-backed). Partner with stakeholders, mentor teammates, document runbooks, and drive data platform reliability and security.

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.

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.

Lead site-based CSA activities for data centre projects: manage contractors, ensure compliance with design, safety and quality, coordinate stakeholders, produce reports, and support project leadership.