Top Data Engineer Jobs in Johor Bahru

Design, build, and operate the organization’s data platform across ingestion, transformation, orchestration, warehousing, and cloud infrastructure. Develop reliable batch and streaming pipelines, data models, contracts, quality checks, governance, privacy controls, and observability. Partner with analytics, research, product, and engineering teams to translate requirements into trustworthy data systems. This is a six-month contractor assignment requiring advanced SQL and Python, modern warehouse, orchestration, infrastructure, and data modeling expertise.

Design, build, and operate the organization’s data platform, including data models, batch and streaming pipelines, orchestration, warehouses, cloud infrastructure, and governance controls. Ensure reliable, observable, high-quality data through contracts, monitoring, privacy protections, and anonymization. Collaborate with analytics, research, product, and engineering teams to translate requirements into scalable data solutions.

Supports and manages cloud-based big data platforms, ETL tools, databases, repositories, and data pipelines. Responsibilities include monitoring, troubleshooting production issues, developing diagnostic tools, optimizing analytics systems, managing support agents, maintaining SLAs, improving processes, and preventing recurring incidents. The role requires Azure big data expertise, programming experience in Python, Java, or Scala, advanced SQL, large-scale data processing knowledge, Power BI and Alteryx experience, strong communication, and ITIL knowledge.

Support the design, development, and optimization of data pipelines, ETL/ELT processes, data models, and cloud-based data solutions using Databricks, Python, and SQL. Perform data quality validation, documentation, testing, deployment, and troubleshooting. Collaborate with engineers, architects, analysts, and stakeholders while exploring AI-assisted development tools, generative AI, and prompt engineering for data engineering use cases.

Develop robotics datasets and evaluations for embodied AI systems. Responsibilities include defining data schemas, annotations, quality standards, collection protocols, validation tools, and review workflows. The role also involves running experiments to assess how data quality and structure affect model performance, collaborating with research, engineering, vendors, and customers, and taking research tools from conception through deployment.

Lead scalable data engineering solutions using Cognite Data Fusion, including integrations, data extraction, modeling, cleansing, pipelines, and analysis. Collaborate with data scientists, architects, project managers, customers, and partners to deliver industrial data solutions. Conduct code reviews, apply DevOps and engineering best practices, contribute to Cognite tools and SDKs, and help prioritize product offerings based on customer needs.

Designs and maintains enterprise data platforms, scalable pipelines, data models, cloud analytics environments, and AI-enabled solutions. Develops generative AI and RAG use cases, vector search, AI agents, workflow orchestration, integrations, and enterprise decision-support capabilities. Requires strong Python and SQL skills, experience with production data engineering, cloud platforms, semantic data models, AI governance, and tools including Microsoft Fabric, Azure AI Foundry, Copilot, OneLake, AWS Redshift, and Amazon Bedrock. This is an onsite role in Johor Bahru or Penang.

Lead HUD's data quality strategy for RL training data: build QC systems, validate synthetic data at scale, design evaluation experiments, partner with researchers and vendors, convert research insights into production validation pipelines and tools, and mentor research 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 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.