Top Data Engineer Jobs in George Town

Provide L2 operational support for database systems, including incident, request, change, and problem management. Install, upgrade, patch, monitor, secure, and troubleshoot databases while maintaining availability and service-level targets. Manage access and backups, improve monitoring and operational procedures, create database reports and dashboards, and participate in 24/7 shift coverage and major incident response. Use AI and agentic solutions to automate workflows and improve IT operations reliability.

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.

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.

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.

Analyzes quality and EHS data from multiple sources, develops Power BI dashboards and reports, identifies trends and anomalies, applies statistical and predictive modeling techniques, integrates TQM systems with analytics platforms, conducts risk assessments, and presents actionable recommendations to stakeholders and executives.

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.

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 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 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.