Associate Architect

National University of Singapore; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

The National University of Singapore is seeking an Associate Architect to lead a team of data engineers and design robust data platforms and pipelines. This role involves driving agile delivery, ensuring data quality, and implementing AI-driven practices. Applicants should have extensive technical lead experience and strong skills in cloud platforms, Python, and distributed data processing techniques. A focus on mentorship and collaboration with product teams is essential. A competitive salary and opportunities for professional growth are offered.

Qualifications

• 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.
• Experience using AI tools to enhance engineering productivity.
• 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 verbal, written, and stakeholder communication skills.

Responsibilities

• Lead, mentor, and grow a team of data engineers.
• Drive agile delivery, conduct code reviews, and promote engineering best practices.
• Design end-to-end data engineering solutions.
• Provide technical leadership to solve complex engineering challenges.
• Ensure strong data quality, reliability, and observability.
• Lead the adoption of AI-assisted engineering practices.

Skills

Cloud data platforms

Python

SQL

Distributed data processing (e.g., Spark)

Data orchestration tools

Data quality practices

AI tools

Data modelling

System design and architecture

Problem-solving skills

Communication skills

Tools

Microsoft Fabric

Databricks

Informatica

Apache Spark

Trino

ClickHouse

DuckDB

Job description

Job Title: Associate Architect

Location: Kent Ridge Campus, NUS Information Technology

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.

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 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 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