About NUS IT
NUS Information Technology is the cornerstone to providing reliable, high-performance and secure IT solutions and effective IT governance for the campus. Here at NUS IT, we aim to transform NUS into a borderless computing community providing knowledge at its fingertips by enhancing the use of effective applications and services for teaching and learning.
We drive a culture that is forward-looking. With a strong passion for IT, our people are always striving to improve, push boundaries and innovate with a "can-do" attitude. We embrace collaboration, open communication and knowledge sharing. If you see yourself thriving in a dynamic environment and breaking new grounds with innovative ideas, you will find yourself at home in NUS IT.
As part of our team, you can look forward to an empowered work environment that allows you to take charge of your own career path. We provide competitive remuneration as well as flexible work arrangements to enable your growth and development. We pride ourselves on our diverse workforce and are committed to transforming NUS into a leading global University shaping the future.
Job Description
We are looking for a Data Engineering Lead to design, build, and scale robust data platforms and pipelines. You will lead and guide a team of data engineers to deliver reliable, secure, and high-quality data systems that support analytics, AI, and application consumption.
Duties and Responsibilities
Team Leadership
- Lead, mentor, and grow a team of data engineers
- Drive agile delivery, conduct code reviews, and promote engineering best practices
- Collaborate with data product teams and stakeholders to prioritize initiatives
Technical Leadership
- Design end-to-end data engineering solutions
- Provide technical leadership to solve complex engineering challenges
- Ensure strong data quality, reliability, and observability across pipelines
- Stay current with emerging technologies to drive continuous improvement and innovation
- Lead the adoption of AI-assisted engineering practices across the development lifecycle
- Drive the use of AI tools (e.g., copilots, agents) to enhance engineering productivity and quality
Data Engineering
- Build and maintain data pipelines and consumption layers (e.g., APIs, databases)
- Develop and manage data lakehouses and data warehouses
- Implement streaming and real-time data solutions where required
- Enable data readiness for model training, feature engineering, and inference workflows
- Apply AI-driven data engineering practices in day-to-day development
- Use AI to generate data engineering artifacts and automate workflows from requirements to production-ready outputs
Quality Assurance & Governance
- Establish testing and quality control practices to ensure reliable data delivery
- Ensure alignment with university regulatory and compliance requirements
Qualifications
Must Have
- Previous technical lead experience
- Strong experience with cloud data platforms
- Proficiency in Python with strong SQL skills
- Experience with distributed data processing (e.g., Spark)
- Hands-on experience with data orchestration tools
- Hands-on experience with data quality practices (testing, validation, and monitoring)
- Experience with AI-driven data engineering lifecycle practices
- Experience using AI tools (e.g., copilots, agents) to enhance engineering productivity and quality
- Experience supporting data pipelines for analytics and/or AI/ML use cases
- Solid understanding of data modelling and data warehousing concepts
- Proven ability in system design, architecture, and leading engineering teams
- Strong problem-solving and critical thinking skills
- Strong verbal, written, and stakeholder communication skills
Nice to Have
- 12+ years of experience in data engineering or related data roles
- Experience with enterprise and open-source data platforms (e.g., Microsoft Fabric, Databricks, Informatica, Apache Spark, Trino, ClickHouse, DuckDB)
- Experience with CI/CD practices for data pipelines
- Exposure to real-time/streaming and event-driven architectures
