Senior Associate Director (Data Platform).

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 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.

https://nusit.nus.edu.sg/

Job Description

We are seeking an experienced Data Platform Lead to oversee data architecture and data platform teams in NUS.

The role will be responsible for leading and guiding teams in the development of high-quality data platforms, ensuring they meet business needs and align with NUS strategic goals. The role will also champion the implementation and adherence to best practices across all stages of the data platform delivery lifecycle, including requirements analysis, design, coding, testing, deployment, and maintenance.

This role will manage a team of ~10 data engineers and modellers handling data platforms such as data lake, data warehouse, and MDM hub development with a plan for future growth. This role will also play a big part to transform the current data platform technologies into a more modern stack, potentially cloud based to support both analytics, AI and microservices.

This is a hands-on leadership role and the candidate should have been on active hands-on development at least 5 years prior.

Duties and Responsibilities

Data Architecture
• Design the evolution of current data platform.
• Create, manage, and document optimal data pipeline architecture.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from data sources.
Technical Expertise
• Define and champion the direction for data platforms and their technologies, including their framework, architecture, standards, and guidelines.
• Create, manage, and document data pipelines in the data pipeline solution and keep them in line with business needs.
• Provide technical guidance and expertise to teams, helping to solve complex technical challenges.
• Stay abreast of emerging technologies and industry trends to drive innovation within the company.
• Supervise the design of data models and database structures for both operational and analytical systems.
• Ensure adherence to best practices in design, development, testing, and maintenance.
Leadership and Team Management
• Lead and mentor teams, fostering a culture of innovation, collaboration, and excellence.
• Provide direction and guidance to teams in managing the full data lifecycle.
• Develop and implement strategies to enhance team performance and productivity.
• Foster collaboration and high-performance culture within the team.
Delivery Management
• Ensure timely and high-quality product platforms delivery, aligning with project objectives, scope, and timelines.
• Oversee the design and implementation of end-to-end data platform solutions to meet the university’s needs.
• Oversee the exploration, deployment, and integration of new technologies into the university's data infrastructure.
Quality Assurance
• Implement quality control and testing procedures to guarantee the delivery of high-quality data platforms.
• Direct the assessment and implementation of data quality solutions to improve accuracy, usability, and reliability of data across all data platforms.
• Ensure all data platforms align with the university's regulatory and compliance requirements.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• Minimum of 12 years of experience in technical leadership roles, with a strong emphasis on data platforms architecture, engineering, and technology management.
• Proven ability to lead and inspire cross-functional teams, promoting collaboration and achieving project objectives.
• Exceptional problem-solving and critical-thinking skills, with a proven track record of effectively addressing technical challenges and risk mitigation.
• In-depth knowledge of quality assurance processes, encompassing testing methodologies, and quality control procedures.
• Demonstrated strategic thinking and planning abilities, capable of aligning technical projects with organizational goals and market demands.
• Relevant experience in designing, developing, and supporting data platforms, having successfully completed at least five full cycles of the SDLC in data platforms delivery
• 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.

Technical Expertise
• Strong working experience in end-to-end development of data lakes and data warehouses, preferably with experience in Informatica.
• Strong working experience in Azure cloud.
• Strong working experience in Azure Fabric – specifically Data Factory, Data Engineering, OneLake (Data Lake Storage) and Data Warehouse.
• Strong data modelling and database design working experience for transactional and analytical systems.
• Strong MS SQL and Oracle experience, including querying and tuning large, complex data sets and performance analysis
• Strong working experience in master data management
• Strong knowledge in IT infrastructure.
• Working experience in big data and DataSecOps is an added advantage.