Big Data Engineer – Assistant (SGUnited)
Internship SINGAPORE IT development
Job description
Traineeship Description:
This position reports to Big Data Manager. Aviva Ltd is committed to an employee-orientated, high performance culture that emphasises empowerment, quality, continuous improvement, and the recruitment and on-going development of a superior workplace.
Specific Responsibilities:
Trainee to be involved in assisting to:
1. Assist in migration of on-premise data applications into AWS.
2. Create data pipelines by ingesting raw data sets into Data lake for Analytics purpose.
3. Create transformations on the Data as required by Data Lake consumers i.e., Data scientists, Other departments in Aviva, Data Analysts, Dashboards.
4. Automate the creation of application Infrastructure and configuration using IaaS-Infrastructure as a Service tools.
5. Create and Monitor DevOps pipelines for the data applications both in on-premises and on the Cloud.
Technical Skills and Competencies Trainee will learn during SGUnited Traineeship Programme:
1. Active participation in supporting Big Data platform, Data Lake projects and Cloud Migration Projects.
2. Know how to define & implement data integration and workflow framework that provides for the loading of data, data integration, aggregations, joins and etc.,
3. Able application support for IT related problems in the area of data processing workflows.
4. Learn the architecture of on-premise Data Lake application present in Aviva.
5. Learn the automation of Infrastructure creation and automation.
6. Learn and setup DevSecOps pipelines for data applications.
7. Learn how to communicate relevant information clearly and effectively in written and oral communication through presentation slides and documentation
Highest Qualification:
Degree
Duration of Traineeship/s:
9 months
Eligibility Criteria for SGUnitedTraineeships:
Singapore Citizen or Permanent Resident; and
a. Graduated or graduating in calendar year 2019 or 2020 from ITEs, polytechnics, universities, or other educational institutions (e.g. private universities and overseas institutions); or
b. Graduated earlier from above institutions and completed National Service in 2019 or 2020
c. Mid-career individuals from any qualification level can apply.
MCF ID:
MCF-2020-0168166