Role 1: Senior Data Engineer/AWS Migration Lead
Key Responsibilities:
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. AWSAnalytics 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
- Understanding of AWS data lake architecture and analytics pipelines
4. Data Management and Processing
- Strong expertise in data analysis, cleaning, and transformation processes
- Strong expertise in data analysis, cleaning, and transformation processes
- Proficiency in SQL for complex data queries and analysis
- Knowledge of data quality assessment and validation techniques
5. Data Governance and Architecture
- Ability to guide users in developing data taxonomy and classification frameworks
- Experience in establishing data naming conventions and metadata standards
- Knowledge of data governance principles for scalable analytics platforms
- Skills in designing data models that support future analytical requirements
6. Stakeholder Management and Business Acumen
- Experience in stakeholder engagement and business requirements gathering
- Ability to conduct user interviews and translate business needs into technical solutions
- Understanding of HR business processes and workflows (preferred)
- Experience in change management and user adoption strategies
7. Communication and Collaboration
- Strong communication skills for working with non-technical stakeholders
- Ability to present complex data insights in clear, actionable formats. Experience in training end-users and creating documentation
- Ability to adapt solutions for different organisational requirements and contexts
