Senior Executive, Data Engineer
Posted
Summary
A hands-on early-career cloud/data engineer in SBS Transit's Digital & AI Office, building secure AWS platforms and batch/streaming data pipelines (Glue, Redshift, Athena, S3, Lambda) that power AI initiatives, using Terraform/CDK, Python and SQL, with a security-first, governance-focused approach.
Job Summary
We are looking for an
AI Data/Platform Engineer
to help build and operate the secure AWS platforms and data pipelines that power digital and AI initiatives across the organisation. Based in the
Digital & AI Office (DAIO) , this is a hands‑on role for an early‑career engineer. You will turn reference architectures, standards and guardrails into working infrastructure and automation, enabling teams to innovate while remaining secure, scalable and compliant. Working alongside senior architects, you will take growing ownership of AWS environments, including sandbox environments where new AI use cases are developed and tested. This role suits someone with a builder's mindset, a security‑first approach, and the discipline to deliver well‑documented and reliable solutions. Key Responsibilities
Cloud Platform Build & Operations
Provision and maintain AWS infrastructure and workloads (VPC, EC2, S3, RDS, Lambda, ECS/EKS) in accordance with approved reference architectures.
Monitor platform health, performance and availability using CloudWatch and related tools.
Support incident management, troubleshooting and root‑cause analysis.
Track cloud usage and recommend right‑sizing and cost optimisation opportunities.
Data Platforms & Engineering
Build and maintain batch and streaming data pipelines using AWS Glue, Redshift, Athena, S3 and Lambda.
Design and optimise data models, including data lake and dimensional modelling approaches.
Apply data quality, lineage and classification controls to support analytics and AI use cases.
Write and optimise SQL queries against analytical and operational data sources.
Infrastructure as Code & Automation
Develop and maintain Infrastructure as Code (Terraform, CloudFormation or AWS CDK).
Support CI/CD pipelines for infrastructure and platform deployments.
Automate operational processes using Python, Bash or AWS‑native services to improve efficiency and reduce manual effort.
Security, Governance & Compliance
Implement and maintain cloud guardrails across a multi‑account AWS environment, including AWS Organizations, Control Tower and Service Control Policies.
Manage IAM roles, access controls, encryption keys and secrets using least‑privilege principles.
Apply architecture standards, tagging policies and data protection controls in day‑to‑day operations.
Support audits, risk assessments and governance reviews by maintaining appropriate evidence and documentation.
Work closely with cyber security teams to ensure solutions are secure by design.
AI Platform & Sandbox Support
Support the setup and administration of enterprise AI and digital sandbox environments with appropriate security, monitoring and access controls.
Enable data and AI/ML workloads on platforms such as Amazon Bedrock, SageMaker and data lake services.
Support the transition of successful AI use cases from experimentation into production environments.
Documentation & Collaboration
Maintain architecture diagrams, runbooks, templates, standards and operational documentation.
Participate in architecture reviews and contribute to knowledge sharing across the Digital & AI Office.
Collaborate with architects, engineers, vendors and business stakeholders to deliver platform capabilities.
Job Requirements
Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related discipline.
0-3 years of experience in cloud, infrastructure, DevOps, platform engineering, data engineering, or related technical roles. Relevant internships and project experience are welcome.
Hands‑on experience with AWS services such as IAM, VPC, EC2, S3, RDS, Lambda, and monitoring tools.
Experience building data pipelines, writing SQL, and supporting analytics or AI workloads.
Knowledge of Infrastructure as Code (Terraform, CloudFormation, or AWS CDK) and automation using Python, Bash, or PowerShell.
Understanding of cloud security principles, including identity and access management, encryption, logging, and monitoring.
Familiarity with Linux, networking fundamentals, Git, and CI/CD practices.
Strong analytical and problem‑solving skills with the ability to work independently and collaboratively.
Good communication skills and the ability to explain technical concepts to both technical and non‑technical stakeholders.
AWS certifications and exposure to AWS data, security, container, or AI/ML services (e.g., Glue, Redshift, Bedrock, SageMaker, ECS, EKS) will be an advantage.
Awareness of governance requirements and regulatory frameworks such as PDPA and the Cybersecurity Act is preferred.
By submitting this application for this position, you acknowledge that you have read the Data Protection Policy for Job Applicants (the “Policy”) of SBS Transit Ltd and its subsidiaries, affiliates and related corporations (‘SBST”) and consent to: a. The collection, use and disclosure of your personal data by SBST for the purposes of your application and potential employment with SBST and the purposes set out in the Policy: and b. SBST’s retention of your personal data for 2 years for consideration of future job opportunities (where applicable) from the date of submission of application.
We are looking for an
AI Data/Platform Engineer
to help build and operate the secure AWS platforms and data pipelines that power digital and AI initiatives across the organisation. Based in the
Digital & AI Office (DAIO) , this is a hands‑on role for an early‑career engineer. You will turn reference architectures, standards and guardrails into working infrastructure and automation, enabling teams to innovate while remaining secure, scalable and compliant. Working alongside senior architects, you will take growing ownership of AWS environments, including sandbox environments where new AI use cases are developed and tested. This role suits someone with a builder's mindset, a security‑first approach, and the discipline to deliver well‑documented and reliable solutions. Key Responsibilities
Cloud Platform Build & Operations
Provision and maintain AWS infrastructure and workloads (VPC, EC2, S3, RDS, Lambda, ECS/EKS) in accordance with approved reference architectures.
Monitor platform health, performance and availability using CloudWatch and related tools.
Support incident management, troubleshooting and root‑cause analysis.
Track cloud usage and recommend right‑sizing and cost optimisation opportunities.
Data Platforms & Engineering
Build and maintain batch and streaming data pipelines using AWS Glue, Redshift, Athena, S3 and Lambda.
Design and optimise data models, including data lake and dimensional modelling approaches.
Apply data quality, lineage and classification controls to support analytics and AI use cases.
Write and optimise SQL queries against analytical and operational data sources.
Infrastructure as Code & Automation
Develop and maintain Infrastructure as Code (Terraform, CloudFormation or AWS CDK).
Support CI/CD pipelines for infrastructure and platform deployments.
Automate operational processes using Python, Bash or AWS‑native services to improve efficiency and reduce manual effort.
Security, Governance & Compliance
Implement and maintain cloud guardrails across a multi‑account AWS environment, including AWS Organizations, Control Tower and Service Control Policies.
Manage IAM roles, access controls, encryption keys and secrets using least‑privilege principles.
Apply architecture standards, tagging policies and data protection controls in day‑to‑day operations.
Support audits, risk assessments and governance reviews by maintaining appropriate evidence and documentation.
Work closely with cyber security teams to ensure solutions are secure by design.
AI Platform & Sandbox Support
Support the setup and administration of enterprise AI and digital sandbox environments with appropriate security, monitoring and access controls.
Enable data and AI/ML workloads on platforms such as Amazon Bedrock, SageMaker and data lake services.
Support the transition of successful AI use cases from experimentation into production environments.
Documentation & Collaboration
Maintain architecture diagrams, runbooks, templates, standards and operational documentation.
Participate in architecture reviews and contribute to knowledge sharing across the Digital & AI Office.
Collaborate with architects, engineers, vendors and business stakeholders to deliver platform capabilities.
Job Requirements
Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related discipline.
0-3 years of experience in cloud, infrastructure, DevOps, platform engineering, data engineering, or related technical roles. Relevant internships and project experience are welcome.
Hands‑on experience with AWS services such as IAM, VPC, EC2, S3, RDS, Lambda, and monitoring tools.
Experience building data pipelines, writing SQL, and supporting analytics or AI workloads.
Knowledge of Infrastructure as Code (Terraform, CloudFormation, or AWS CDK) and automation using Python, Bash, or PowerShell.
Understanding of cloud security principles, including identity and access management, encryption, logging, and monitoring.
Familiarity with Linux, networking fundamentals, Git, and CI/CD practices.
Strong analytical and problem‑solving skills with the ability to work independently and collaboratively.
Good communication skills and the ability to explain technical concepts to both technical and non‑technical stakeholders.
AWS certifications and exposure to AWS data, security, container, or AI/ML services (e.g., Glue, Redshift, Bedrock, SageMaker, ECS, EKS) will be an advantage.
Awareness of governance requirements and regulatory frameworks such as PDPA and the Cybersecurity Act is preferred.
By submitting this application for this position, you acknowledge that you have read the Data Protection Policy for Job Applicants (the “Policy”) of SBS Transit Ltd and its subsidiaries, affiliates and related corporations (‘SBST”) and consent to: a. The collection, use and disclosure of your personal data by SBST for the purposes of your application and potential employment with SBST and the purposes set out in the Policy: and b. SBST’s retention of your personal data for 2 years for consideration of future job opportunities (where applicable) from the date of submission of application.
Skills
- AI
- Analytics
- Athena
- Automation
- AWS
- AWS Bedrock
- Aws Glue
- Bash
- CDK
- CI/CD
- Cloud
- Cloud Security
- CloudFormation
- CloudWatch
- Cybersecurity
- Data Engineering
- Data Lake
- Data Pipelines
- Data Quality
- DevOps
- Dimensional Modeling
- EC2
- ECS
- EKS
- Git
- IAM
- Infrastructure as Code
- Lambda
- Linux
- Machine Learning
- Networking
- PowerShell
- Python
- RDS
- Redshift
- Risk Assessment
- S3
- SageMaker
- SQL
- Terraform
- VPC