1. Migration & Technical Implementation:

• Lead migration of on-premises and SharePoint-based data infrastructure to AWS Data Analytics Platform (DAP)
• Collaborate with AWS teams to develop comprehensive migration strategies and implementation plans
• Re-architect existing Python scripts and UiPath automation workflows for AWS SageMaker or Glue scripts
• Design and implement robust data pipelines and ETL processes within AWS environment
• Migrate Tableau dashboards to AWS QuickSight whilst maintaining full functionality
• Establish data connections from multiple sources (HRPS, Gateway, SharePoint, Microsoft Lists, FormSG, MS Access)
• Ensure seamless transition with zero disruption to existing data operations

2. Documentation & Knowledge Transfer:

• Create comprehensive documentation for all new AWS processes and workflows
• Develop training materials and conduct knowledge transfer sessions for end users
• Support HR officers in accessing and utilising dashboards in the new AWS environment
• Conduct thorough testing and validation of migrated systems

Required Skills:

1. AWS Services

• Extensive experience with AWS services (SageMaker, QuickSight, Athena, Lambda, data pipelines).
• Experience using AWS services in Python and Command Line Interface
• Proficiency in serverless architecture design and Lambda function development.

2. Infrastructure as Code (IaaC)

• Experience in Infrastructure-as-Code (eg. CloudFormation, YAML, JSON infrastructure scripts)
• Lambda function provisioning and management through IaaC templates
• Integration of serverless components with traditional infrastructure resources

3. Programming and Automation Skills

• Proficiency in Python programming and UiPath automation
• Experience developing and deploying Lambda functions for data processing and automation
• Understanding of event-driven architecture and serverless computing patterns

4. Data Visualisation and Analytics

• Strong background in Tableau and QuickSight dashboard development
• Experience with ETL processes and data pipeline design
• Knowledge of serverless data processing workflows using Lambda

5. DevOps and Collaboration

• Experience working with DevOps stack (eg. Ship-hats, GitLab, Nexus Repo etc)
• Understanding of CI/CD pipelines for both application code and infrastructure deployment
• Experience with infrastructure change management including security groups and network ACLs

6. Technical writing and documentation skills

7. Training delivery and user support capabilities

Role 2: Business Intelligence Developer & Dashboard Specialist

Key Responsibilities:

1. Dashboard Development & Business Intelligence:

• Gather and analyse stakeholder requirements for new dashboard development and business insights
• Understand the business requirements and propose the suitable solution by analysing suitable services that can facilitate the requirements as a whole.
• Design and develop additional dashboards and analytical workflows supporting business decision-making
• Collect, clean, and transform data from various sources to support new analytical requirements
• Collaborate with stakeholders to iteratively develop and refine dashboard solutions
• Create user-friendly interfaces and visualisations enhancing business workflow efficiency

2. Data Analysis & Future Scaling Support:

• Ensure dashboard performance optimisation and user accessibility
• Provide ongoing support and enhancements based on user feedback
• Support data validation and quality assurance during migration process
• Assist with preparation for Phase 3 scaling initiatives for statutory boards
• Support customisation of scripts and dashboards for different organisational contexts

Required Skills:

1. Strong experience in business intelligence and dashboard development

2. Data Visualisation and Analytics

• Strong background in Tableau and QuickSight dashboard development and performance optimisation
• Experience with ETL processes and data pipeline design
• Experience designing intuitive user interfaces and data storytelling through visualisations
• Knowledge of data visualisation best practices and user experience principles

3. AWS Analytics and AI Services

• Knowledge in AWS analytics services (SageMaker, QuickSight, Athena, Lambda)
• Knowledge in using AWS services through Python SDK and Command Line Interface (CLI)
• Experience with serverless data processing workflows and Lambda functions for data transformation