Job Description

OverviewAt NUHS Academic Information Office - Management Decision Support, we support the organisation in managing data and drawing meaningful insights from data. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimising data systems and building them from ground up. You will work in close partnership with cluster-wide data science and analytics teams by supporting the development of cluster wide data infrastructure.*Data Engineering (DE) involves the designing, building and managing of infrastructure for collecting, storing and processing large volumes of data efficiently. DE transforms raw data into data assets and is a foundational function of effective data analytics and AI capabilities.Key ResponsibilitiesYou will be responsible for the following:

• Lead in the design and implementation of flexible and scalable next-generation data architecture.
• Optimise cloud-based data pipelines to integrate and transform structured and unstructured complex data from source systems into a cohesive data platform.
• Ensure data interoperability across disparate systems, ensuring seamless data flow, accessibility and discoverability.
• Develop and monitor data quality related key performance indicators. Devise process improvements and automated audits.
• Lead detailed documentations of data definitions, data schemas, data lineage, data flow, data lifecycle.
• Access and use of Data in compliance with NUHS data policies and legal requirements.

• Minimum Bachelor\'s degree in Computer Science, Software Engineering, Cloud Engineering, Information Systems, Engineering or related technical fields. Relevant data related certifications would be a bonus.
• Minimum 3 year of job experience in data engineering.
• Proficient in the use of object-oriented/object function scripting languages (e.g. SQL, Python, Java, Scala).
• Solid understanding of ETL and ELT principles. Good knowledge of SQL disciplines and writing simple to complex SQL queries for data retrieval and analysis.
• Hands-on experience with data processing tools or frameworks, i.e. Pandas, SKlearn, Apache Spark, Hadoop or similar technologies. Knowledge of real-time data streaming pipeline (i.e. Kafka) is a bonus.
• Working experience with cloud platforms and their related services, AWS, Google Cloud Platform, Azure, etc. Knowledge of AWS services - S3, Lambda, Airflow, Redshift, Glue, Athena, Sagemaker, Aurora, Cloudwatch, SQS, would be a bonus.
• Experience with containerisation and orchestration tools (e.g. Docker, Kubernetes).
• Ability to write clean and efficient code.
• Opportunity to undergo EMR system training provided by the company.
• Effective communicator with ability to explain complex technical concepts to non-technical stakeholders.
• Can-do attitude and ability to work independently, comfortable with ambiguity.
• Thrive in problem solving, learning and applying new knowledge.

National University Health System