Manager/ Senior Manager, Data Engineering & Architecture Department at Public Service Division

Singapore, Singapore, Singapore -

Full Time

Start Date

Immediate

Expiry Date

11 Mar, 26

Salary

0.0

Posted On

11 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Project Management, Python, Power BI, Data ETL, Data Cleaning, Data Modelling, Feature Engineering, Data Governance, Data Quality Assurance, Automated Testing, Data Infrastructure, Machine Learning, Big Data Technologies, Test-Driven Development, Digital Health

Industry

IT Services and IT Consulting

Description

[What the role is] Recognising the efficacy of big data and artificial intelligence in optimising sharper insights and outcomes for public health, the CDOO’s Data Engineering and Architecture department plays a proactive role in driving the design of a citizen-centric data architecture to support the transformation in programme delivery and enablement of a data-driven approach to programme evaluation. We are looking for dynamic and enthusiastic individuals with strong data engineering skills and project delivery experience to join us on this journey to build a more data-driven HPB. You will be pivotal in helping to set up and implement robust data engineering pipelines that can integrate the vast wealth of data HPB has through its numerous data sources. As a Data Engineer in the Chief Data Officer’s Office at HPB, you’ll play a pivotal role in driving technical leadership, operational excellence, service delivery improvements and the growth of data capabilities. You will be instrumental in building scalable, secure, and high-quality data infrastructure that supports HPB’s mission to deliver impactful health programmes and insights. This role requires an individual with experience in data engineering work as well as good communication skills, as you will be expected to interact frequently with users to elicit business requirements. [What you will be working on] Design and implement highly robust, resilient and reliable automated data pipelines for processing lifestyle big data (physical activity, sleep, food, smoking). Architect scalable solutions for managing data requests and develop incremental load strategies with data lineage tracking. Collaborate with the Data Quality Assurance team to implement automated testing and validation frameworks. Ensure accuracy in data delivery and compliance with data governance standards. Provide process improvement recommendations to drive reduction in data service incidents. Create and maintain comprehensive documentation and knowledge management systems. Apply test-driven methodology to develop optimal data ingestion pipeline and tables for strategic datasets and drive data engineering processes related to data ingestion, data imputation, data transformation and integration to facilitate data science and analytics use cases Translate research and analytics questions into data features to facilitate dashboarding, model training, analytics, and data science applications Project manage and be the overall lead for engagement to bring together HPB vendors, partners, IT and business teams to plan, set timelines and drive processes that enable timely delivery of the data engineering pipeline guided by business needs Lead internal cross-functional teams to integrate, process and engineer disparate datasets into structured and meaningful variables to facilitate machine learning and data science use cases Lead the preparation of materials to update senior management periodically on progress of the project and surface issues and challenges for collective deliberation and decision-making [What we are looking for] Bachelor/Masters degree in Computer Science, Engineering or Information Systems with major / project experience in data science and/or business analytics from a recognised university. Professional certifications in data engineering from accredited professional bodies will be highly desirable. Minimum 5 years of relevant project management and delivery experience. Experience in end-to-end deployment of data engineering projects in production environment preferred. Proficient in the use of Python and/or Power BI Experience working on data engineering, and/or database architectural work Experience working on a few of the following component in the data pipeline: data ETL, data cleaning, data modelling, and feature engineering. Able to work in a fast-paced matrix environment, overseeing multiple projects at the same time Good communication skills and able to communicate and express complex data/concepts in a clear and simple-to-understand manner Possess the drive, commitment, and perseverance to do well and have strong intellectual curiosity to learn and seek continuous improvements in the work assigned Take an interest in digital health and healthcare Desirable requirements: Experience in architecting data and IT systems Experience in designing, building, and maintaining batch and real-time data pipelines Experience with Databricks Experience with implementing technical processes to enforce data security, data quality, and data governance Familiarity with government systems and government's policies relating to data governance, data management, data infrastructure, and data security Experience in Big Data technologies e.g. Hadoop and Spark Ecosystems Experience with test-driven development http://jobs.careers.gov.sg The Singapore Public Service plays a key role in the economic growth, progress and stability of Singapore by formulating and implementing government policies, as well as providing key public services. Whether you are a fresh graduate joining the workforce or an experienced professional, the Singapore Public Service offers a great variety of job opportunities for you. The work in the Public Service can be broadly categorised into the following sectors: Economic, Social, Security & External Relations, and Administration & Corporate Development. Be part of the team that shapes the future of Singapore. Log on and take your first step towards a career that matters! Need help? Please click here for assistance. Our team will contact you shortly!

Responsibilities

The role involves designing and implementing robust automated data pipelines and collaborating with various teams to ensure data accuracy and compliance. You will also lead project management efforts to integrate and process disparate datasets for data science applications.