M12

Role Summary

The Data Engineer will support the design, development, and operation of modern data systems and infrastructure for Data Programme. The role involves building scalable and secure data platforms, developing production-grade data pipelines, and enabling analytics, AI, and machine learning use cases across the ecosystem.

The candidate is expected to work closely with Product Managers, Data Scientists, engineers, and business stakeholders to deliver reusable, maintainable, and secure data solutions that support digital transformation objectives.

Key Responsibilities

1. Data Systems and Architecture

• Design, develop, and maintain end-to-end data systems and supporting architecture
• Build and integrate database systems, backend services, and infrastructure components to support business and analytical use cases
• Ensure solutions are designed with strong consideration for scalability, maintainability, reusability, and security
• Contribute to architecture and engineering decisions for data platforms and services

2. Data Engineering and Pipeline Development

• Develop and maintain production-grade ETL / ELT pipelines for ingestion, transformation, and delivery of data
• Build and administer databases and supporting data services for operational and analytical workloads
• Support reliable and efficient data workflows for reporting, analytics, data science, and machine learning applications
• Monitor, troubleshoot, and optimise data processing jobs, database operations, and pipeline performance

3. Cloud, DevOps and Infrastructure

• Develop infrastructure and services using modern cloud engineering practices
• Support backend, infrastructure, deployment, and operational components required for data systems
• Contribute to automation, CI/CD, monitoring, and operational readiness of data platforms
• Ensure secure and resilient deployment practices across environments

4. Cross-functional Delivery

• Work closely with Product Managers, Data Scientists, users, and other engineers to ensure solutions meet user and organisational needs
• Partner with policy and business divisions to support digital transformation initiatives through data and AI methods
• Translate requirements into implementable technical designs and engineering work items
• Participate actively in iterative product and platform delivery

5. Documentation and Support

• Document system designs, architecture decisions, data flows, and operational procedures
• Support knowledge transfer, maintainability, and operational support for delivered solutions
• Collaborate effectively across multidisciplinary teams and contribute to healthy engineering practices
• Support issue investigation, troubleshooting, and enhancement of production systems

Mandatory Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience
• Experience in data systems and architecture development, including databases, backend services, DevOps, and infrastructure engineering
• Experience developing and administering production-grade databases and data pipelines
• Strong understanding of scalable, secure, and maintainable engineering practices
• Strong communication and collaboration skills
• Interest in working on public good and supporting digital transformation in the education domain

• Experience with modern cloud-based data engineering environments
• Experience with backend development and system integration
• Experience with frontend development
• Exposure to data science and machine learning applications
• Familiarity with DevOps, CI/CD, infrastructure automation, and monitoring practices
• Experience working in agile, cross-functional product teams
• Experience in public sector, education, or mission-driven digital delivery environments

Seniority Expectations

Associate Consultant (1-3 Years)

• Supports design, development, and maintenance of data systems under guidance
• Contributes to data pipelines, database tasks, and operational support activities
• Demonstrates sound technical fundamentals and willingness to learn

Consultant (4-6 Years)

• Works independently on assigned engineering tasks and modules
• Designs and develops data pipelines, databases, and infrastructure components of moderate complexity
• Participates actively in technical discussions and cross-functional delivery

Senior Consultant (7 Years and above)

• Takes ownership of end-to-end system and architecture components
• Leads design and implementation of scalable, secure, and reusable data platforms
• Supports technical decision-making and mentors junior team members where needed
• Engages confidently with cross-functional stakeholders across product, business, and technical teams