Zorky CRMZorky CRM
EN|RU
@termdocs
← All jobs

Data Engineer

hybrid7,500 SGDSingapore, SGScore 67.5/1001d ago
Market insights
📊 Data Engineering: salaries and demand on the market
Stack
Data IngestionDesignConstructionimplementing monitoring toolsData PipelineDatabase SystemsRoot Cause Analysiscloud hosting platformData Management ServicesEnterprise ApplicationsLiaise With Technical TeamsCloud-Based Platform
Apply
Upload your CV — we will connect you with the employer directly through our pool.
Send your CV →
Description
Key Responsibilities Design, build, and maintain reliable data pipelines and data-processing workflows. Integrate data from APIs, databases, enterprise applications, cloud services, files, and other source systems. Develop scalable solutions for data ingestion, transformation, storage, processing, and serving. Support data platforms operating across cloud, on-premise, or hybrid environments. Implement appropriate monitoring, data-quality checks, error handling, and operational controls. Automate deployment and operational processes using CI/CD and Infrastructure as Code where applicable. Support production systems, troubleshoot issues, and contribute to root-cause analysis and continuous improvements. Work closely with application, infrastructure, platform, security, and business teams to deliver reliable data solutions. Maintain relevant technical documentation, operational procedures, and engineering standards. Requirements Around 4–7 years or more of relevant experience in Data Engineering, Cloud Engineering, Platform Engineering, DevOps, SRE, or a related technical discipline. Hands-on experience designing, building, or operating production-grade data solutions. Experience with cloud platforms such as AWS and/or Azure. Experience with some of the following areas: Python and SQL ETL / ELT and data pipelines Batch, streaming, CDC, or event-driven processing Data modelling and data quality Cloud data platforms and services Logging, monitoring, telemetry, or observability CI/CD and Infrastructure as Code Docker or containerised environments Good understanding of software engineering practices, system reliability, scalability, security, and production support. Strong problem-solving skills and the ability to work across technical teams. Good to Have Experience working across on-premise and cloud environments. Experience with streaming or messaging technologies such as Kafka or MQ. Experience with Terraform, Ansible, or equivalent automation tools. Familiarity with observability or monitoring platforms such as Grafana, Prometheus, Dynatrace, Elastic, or equivalent. Experience working in large-scale enterprise or Government environments. AWS or Azure certifications.
Employer contacts (email/phone/telegram) are hidden from the public preview — send your CV, and we will connect you directly.
Urgent question? Message @termdocs