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Data Engineer

Middlehybrid6,500 SGD · period not specifiedSingapore, SG2d ago
Market insights
📊 Data Engineering: salaries and demand on the market
Stack
Liaising with cross functional teamsCloud TechnologiesAmazon BedrockTroubleshooting ProceduresAutomated Software Testingreliability monitoringData IntegrationPlatform as a ServiceAzure AI SearchResolve Operational IssuesProduction DeploymentEvent-Driven Architecture (EDA)
Details
Experience
3+ years
Practices
CI/CD, DevOps
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Description
Key Responsibilities Design, develop and implement scalable data and platform solutions across AWS cloud and hybrid/on-premises environments. Build, maintain and optimise production-grade data pipelines, platform services and automation frameworks using Python, PySpark, SQL and cloud-native technologies. Support and enhance enterprise data platforms, including data lakes, lakehouse architectures, metadata management, search platforms and AI services. Develop and maintain CI/CD pipelines, automated testing frameworks and deployment processes to ensure reliable and efficient software delivery. Implement, integrate and support technologies such as OpenSearch, Amazon Bedrock, AgentCore, MCP and related platform services. Monitor and improve platform reliability, security, performance, observability and cost efficiency. Troubleshoot and resolve production issues, perform root-cause analysis and ensure platform stability and operational excellence. Collaborate with cross-functional teams to drive platform modernisation, automation and continuous improvement initiatives. Mandatory Requirements 3–5+ years of hands-on experience building and supporting production-grade data pipelines using SQL, Python and cloud technologies. Practical experience working with AWS and/or hybrid cloud environments. Strong Linux/Unix administration and scripting skills, with experience supporting production systems and troubleshooting operational issues. Strong understanding of ETL/ELT processes, data int
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