Roles and Responsibilities

Maintain the organisation’s data warehouse and analytics platforms on both on-premise data centre as well as on cloud.
Develop automation code for testing and deployment using Azure DevOps, Git and various testing tools for the data platforms.
Liaise with both vender and inhouse team on data warehouse and analytics development platform including SQL databases, MS Sharepoint, Power BI, Tableau, Aurora PostgresSQL and Machine Learning applications on agency data centre.
Perform automated deployments to existing or new infrastructure environments
Build continuous integration and delivery pipeline for applications.
Provide production support and operation for the system during office hours or as and when required after office hours or on weekends for scheduled maintenance and deployments.
Work with the team to support existing system and integration of new components in the system.
Maintain existing infrastructure which includes Windows-based servers, SQL databases, Power BI, Sharepoint, SQL Server Integration Services (SSIS), and Machine Learning Server.
Plan, design, build and maintain development environment which includes SSIS, .net, Visual basic, SSMS, etc.
Liaise with 3^rd party software, hardware and application vendors to manage and resolve incidents and technical issues.

2. Knowledge and Skills

Tertiary Education in relevant fields is preferred.
Hands on experience in setting up and maintaining CI/CD platform, such as Azure DevOps, Git/Github or other related CI/CD tools.
Hands on experience in writing automation scripts for automated deployment for ETL packages, database tables, and analytics programs using R and Python.
Hands on experience in design, implementation, administration and support of data platforms such as SQL and Aurora Postgres database. Related certifications will be an advantage.
Hands on experience in setting up and maintaining a data warehouse/lake solution on the cloud and in a data centre.
Hands on experience in supporting Microsoft technologies, preferably for Business Intelligence and data management using tools such as Microsoft SQL SSIS, Power BI, R, SharePoint.
Experience in one or more of the following:

Building CI/CD pipeline using Azure DevOps, Bamboo, Bitbucket, Sonarqube, Fortify and Nexus
Building data pipelines using Python, AWS Glue, AWS Lambda, SQL Server Integration Services (SSIS)
Unix scripts for secure file transfers
Data security
Secure code review, Automated Testing
Big Data platform, AWS S3
Maintaining visualisation tools such as Power BI or Tableau, and Machine Learning applications
Server Virtualisation (VMWare VSphere family of products) and container technology
Data Virtualisation technology
Agile continuous integration tools
· Good team player.
· Passionate in championing the team to continuously improve and deliver quality software product.

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DevSecOps Engineer