Principal Big Data Engineer Full time
- builds large-scale data processing systems, is an expert in data warehousing solutions and should be able to work with the latest (NoSQL) database technologies.
- Implement/Optimize ETLs to: Capture, cleanse, and augment data from different sources.
- Design and implement a data hub/store to store all the cleansed and organized data.
- Continuous maintenance of data integrity and consistency of the data store, such as DWH.
- Implement and execute data archiving strategy.
- Provide a fast/secure way to access data hub to cater for other analytics purposes.
- Develop big data solution design and data architecture for data management use cases.
- Lead and mentor younger team members.
- Knows how to capture, process, store and access data (ETL), aware of ETL tools such as Talend, Data stage, etc…
- 4+ years of similar experience
- Familiar with DWH, Apache Hadoop, Apache Spark, NoSQL Databases, Machine Learning and Data Mining, Statistical and Quantitative Analysis, SQL, Data Visualization.
- Scripting languages and General purpose Programming Languages, of both traditional and big data.
- Data integration and cleansing.
- Ability to interpret client briefs and prescribe the most appropriate analytical approach to answer the business requirements.
- Experience with BI reporting tools, such as Looker, Qlik, IBM Cognos or Power BI is preferable.
- Problem solving.
- Excellent communication skills to understand reporting requirements from end-users to senior management
- Performance optimization of a data workflow.