Senior Principal / Principal Consultant (Data Platform Engineering)

National University of Singapore

unknownPosted Jan 14, 2026
Posting intelligenceMay be filled, listed long agoReposted 23×, possible evergreen/ghost posting

Skills

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About the role

Job Title: Senior Principal / Principal Consultant (Data Platform Engineering)

University-Level Unit: NUS Information Technology

Faculty/Department-Level Unit: Applications - Applications Architecture & Technology

Employee Category: Executive & Administrative

Location_ONB: Kent Ridge Campus

Posting Start Date: 14/01/2026

Job Purpose

We are seeking an experienced Data Platform Engineer to manage data platform operations, and to design and deliver ELT/ETL frameworks at NUS. The ELT/ETL frameworks comprise of ingestion, orchestration, quality, retention, monitoring, and other related capabilities.

The role will be responsible for addressing stakeholders’ needs regarding data platform operations and ensuring alignment with business requirements. The role will also co-lead the design, development and maintenance of metadata driven ELT/ETL frameworks in NUS.

This is a hands-on role, and the candidate should have at least 5 years of active, hands-on design and development experience.

Role and Responsibilities

Technical Expertise

Participate in the technical design of data platforms and their technologies, including their framework, architecture, standards, and guidelines.

Stay up to date with emerging data platform technologies and industry trends to drive innovation.

Ensure adherence to best practices in ELT/ETL framework design, development, testing, and maintenance.

Provide technical guidance and expertise to the different stakeholders on using the data platform and ELT/ETL frameworks, helping to solve complex technical challenges.

Delivery Management

Design, develop, and maintain metadata-driven ELT/ETL framework to meet the university’s needs.

Ensure timely and high-quality ELT/ETL framework design and delivery, aligned with project objectives, scope, and timelines.

Quality Assurance

Implement quality control and testing procedures to guarantee the high-quality delivery.

Ensure alignment with the university's regulatory and compliance requirements.

Qualifications and Requirements

Must-Have:

Strong working experience in managing enterprise data platform operations.

Strong working experience in end-to-end development of ELT/ETL frameworks, data engineering, and quality solutions for data lakes and data warehouses.

Strong database working experience for transactional and analytics systems, including querying and tuning large, complex data sets and performance analysis.

Strong problem-solving and critical-thinking skills, with a proven track record of effectively addressing technical challenges and risk mitigation.

Strong knowledge of quality assurance processes, encompassing testing methodologies, and quality control procedures.

Strong verbal, written and interpersonal communication skills with the ability to interact and communicate effectively with all levels of management, users, and vendors.

Must be a good team player, proactive in nature, fast learner, highly organized and go-getter attitude with can-do spirit.

Good-to-Have:

Previous technical lead experience.

Working experience with either proprietary Data Engineering tools like Fabric or Informatica, or open-source tools like Apache Iceberg, Apache Paimon, Apache Spark (PySpark), Apache Doris, Trino or Clickhouse or DuckDB over Iceberg.

Working experience with programming languages like Python, Pandas.

Working experience in Data Science.

Working experience in DevOps.

Job requisition ID : 29460

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