April 25, 2024
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Singapore, Singapore, Singapore
April 25, 2024
Apply NowJob description
Data Engineer
The Data Engineer is responsible for designing, constructing, installing, testing, and maintaining highly scalable data management systems. He or she ensures that all data flows smoothly from source to destination so it can be processed and analyzed by users and applications. He or she lays the foundation for data analysis and machine learning by ensuring data is accessible, stored properly and optimized for performance.
Key roles and responsibilities:
Data Acquisition: Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
ETL Development: Design and implement efficient and secure ETL (Extract, Transform, Load) processes, pipelines, and architectures to bring the data into the system from various sources.
Collaboration: Work closely with stakeholders to understand data needs and implement processes to ensure data quality, consistency, and reliability. Perform data validation checks and establish monitoring mechanisms to detect anomalies or issues in the data.
Tool Proficiency: Utilise a variety of languages (e.g., SQL, Python) and tools to work with large datasets and develop data processing systems.
The Data Engineer is responsible for designing, constructing, installing, testing, and maintaining highly scalable data management systems. He or she ensures that all data flows smoothly from source to destination so it can be processed and analyzed by users and applications. He or she lays the foundation for data analysis and machine learning by ensuring data is accessible, stored properly and optimized for performance.
Key roles and responsibilities:
Data Acquisition: Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
ETL Development: Design and implement efficient and secure ETL (Extract, Transform, Load) processes, pipelines, and architectures to bring the data into the system from various sources.
Collaboration: Work closely with stakeholders to understand data needs and implement processes to ensure data quality, consistency, and reliability. Perform data validation checks and establish monitoring mechanisms to detect anomalies or issues in the data.
Tool Proficiency: Utilise a variety of languages (e.g., SQL, Python) and tools to work with large datasets and develop data processing systems.
