Data Engineering Lead

**Posting Start Date**:12/12/2024
About NUS ITWe 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.

We are seeking an experienced Data Engineering Lead to oversee the data engineering team in NUS.

The role will be responsible for leading and guiding teams in the development of high-quality data lakehouse, ensuring they meet business needs and align with NUS strategic goals. The role will also ensure the proper implementation across all stages of the data lifecycle

This role will manage a team of 6 data engineers handling ELT/ETL framework and end-to-end data pipelines from various source systems to data lakehouse with a plan for future growth.
**Responsibilities**:
**Technical Expertise**
- Participate in the technical design of data platforms and their technologies, including their framework, architecture, standards, and guidelines.
- Provide technical guidance and expertise to the team, helping to solve complex technical challenges.
- Stay updated about emerging technologies and industry trends to drive innovation within our organization.
- Ensure adherence to best practices in design, development, testing, and maintenance.

**Leadership and Team Management**
- Lead and mentor the team, fostering a culture of innovation, collaboration, and excellence.
- Provide direction and guidance to the team in managing the full data lifecycle.
- Perform Scrum Master role for the team.
- Develop and implement strategies to enhance team’s performance and productivity.
- Foster collaboration and high-performance culture within the team.

**Delivery Management**
- Ensure timely and high-quality delivery, aligning with project objectives, scope, and timelines.
- Oversee the design and implementation of data lakehouse to meet the university’s needs.

**Quality Assurance**
- Implement quality control and testing procedures to guarantee the high-quality delivery.
- Ensure data lakehouse aligns with the university's regulatory and compliance requirements.

**Qualifications**
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Minimum of 7 years of experience in technical leadership roles, with a strong emphasis on data lakehouse and data engineering solutions.
- Proven ability to lead data engineering teams, promoting collaboration and achieving project objectives.
- 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.
- Relevant experience in designing, developing, and supporting data lakehouse and data engineering solutions.
- 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 Data services, preferably Azure Fabric.
- Strong database working experience for transactional and analytics systems, including querying and tuning large, complex data sets and performance analysis.
- Working experience in big data and DataSecOps is an added advantage.

**More Information**

Location: Kent Ridge Campus

Organization: NUS Information Technology

Department : Applications - Applications Architecture & Technology

Employee Referral Eligible: Yes

Job requisition ID : 27097