
Data Engineer (Big Data)
Spearing Executive Search · Singapore
Strong hiring record · median 52 days open
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- Open 84 days
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Data Engineer (Big Data) - Spearing Executive Search | Career Page
Data Engineer (Big Data)
Singapore, Singapore, Singapore S$ 4,500.00 - 6,000.00 (Singapore Dollar)
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Job Openings Data Engineer (Big Data)
About the job Data Engineer (Big Data)
Job Description
Are you the Data Engineer we are looking for? We are looking for someone with the ability to be sensitive to key details, someone who is able to think in and out of the box in order to improve data reliability and quality in effective and efficient ways.
As a Data Engineer, you will be analyzing raw data and maintaining and developing datasets in order for the businesss data to improve in quality and efficiency. This means having a keen eye for detail will definitely be of great benefit, as it will allow you to be able to view the businesss data and evaluate its needs, and also find different ways for data acquisition.
About the role
As the businesss Data engineer, having self initiative and the ability to prioritize will be of great importance, as you will need to be able to think of different ways for the company to efficiently and effectively acquire raw data. This also requires you to be fluent in different transformation tools, techniques and algorithms.
Job Responsibilities
Recognize the businesss need for data
- Interpret trends and patterns in order to advise the business on data acquisition strategies
- Conduct complex data analysis and report on its results while being able to compile them and prepare the data for prescriptive and predictive modeling.
Ensure smooth operations of data infrastructure
- Find ways to seamlessly integrate data between systems with low-risk
- Have self initiative to find solutions to blockers and issues
- Be able to guide information management standards to align with the businesss information security standards or be able to set a standard
Building and maintaining data pipelines
- Be able to transform and integrate data into scalable data repository (cloud, data lake, data warehouse etc.)
- Test data pipelines for its reliability and scalability and ease of handling while also ensuring its performance and reliability are in place.
- Possibly automate data collection and analyzing of data
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