Associate Architect (NUS IT)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

National University of Singapore invites an experienced Data Platform Engineer to oversee data platform operations and to design and deliver ELT/ETL frameworks for ingestion, orchestration, quality, retention and monitoring. This hands-on role requires at least 5 years of active design and development experience.

You will work closely with stakeholders to ensure data solutions meet university needs and regulatory requirements, providing guidance on best practices and technical risk mitigation

Qualifications

• Must-Have: Strong working experience in managing enterprise data platform operations.
• Must-Have: Strong working experience in end-to-end development of ELT/ETL frameworks, data engineering, and quality solutions for data lakes and data warehouses.
• Must-Have: Strong database working experience for transactional and analytics systems, including querying and tuning large, complex data sets and performance analysis.
• Must-Have: Strong problem-solving and critical-thinking skills, with a proven track record of effectively addressing technical challenges and risk mitigation.
• Must-Have: Strong knowledge of quality assurance processes, encompassing testing methodologies, and quality control procedures.
• Must-Have: Strong verbal, written and interpersonal communication skills with the ability to interact and communicate effectively with all levels of management, users, and vendors.
• Must-Have: 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.
• Good-to-Have: 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.
• Good-to-Have: Working experience with programming languages like Python, Pandas.
• Good-to-Have: Working experience in Data Science.
• Good-to-Have: Working experience in DevOps.

Responsibilities

• 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.
• 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.
• Implement quality control and testing procedures to guarantee the high-quality delivery.
• Ensure alignment with the university's regulatory and compliance requirements.

Skills

Data platform ops

ELT/ETL development

Data lakes/warehouses

SQL tuning

Quality assurance

Stakeholder comms

Team player

Tools

Fabric

Informatica

Apache Iceberg

Apache Spark (PySpark)

Apache Doris

Trino

ClickHouse

DuckDB

Python

Pandas

DevOps tooling

Job description

We regret that only shortlisted candidates will be notified.

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.