Data Scientist

Job Responsibilities :

• Guide and plan data engineering processes.
• Lead technical discussions with the data engineering team and stakeholders
• Lead and advise agency on data engineering strategy, architecture, and implementation aligned with the Digital Government Blueprint (DGB2.0).
• Provide technical leadership across multiple product teams by establishing data architecture standards and developer operations best practices that ensure consistency, quality, and enhanced system reliability across all data initiatives.

Mentor and train the data engineering team to build their capabilities in the following:

Data Infrastructure Support

•   Assist in designing and developing data pipelines and architectures to collect, process, harmonize and store data from various source systems across client's digital products

•   Support the building of data pipelines that integrate data from multiple client's platforms and services

•   Help maintain data lakes and database infrastructure to support analytical, reporting, and AI workloads across the client's ecosystem

Data Quality and Monitoring

•  Implement data validation, cleansing, and normalisation processes under supervision to ensure data quality and integrity

•  Monitor data pipelines and systems to identify potential issues and performance bottlenecks

•  Assist in maintaining data governance frameworks that support compliance and data security requirements

System Maintenance and Documentation

•  Support the maintenance of data infrastructure supporting client's digital products

•  Assist in troubleshooting and resolving data-related issues under guidance from senior team members

•  Create and maintain documentation of data engineering processes and system configurations

Collaboration to facilitate business requirements

•   Work closely with senior data engineers, product teams, analysts, and stakeholders to understand business data requirements into technical specifications and scalable solutions

•  Design, develop and deploy data tables, visualisation and marts for business reporting

Professional Development

•   Stay current with emerging technologies and trends in data engineering through training and mentorship

•   Participate in continuous learning opportunities to develop technical skills and domain knowledge

•   Contribute to process improvements and suggest enhancements to existing data systems

•   Participate in knowledge sharing sessions and contribute to team learning initiatives

Job Requirement :

Skills & Knowledge:

Technical Skills

•   Proficiency in at least one programming language such as Python, Java, or Scala for data processing and scripting

•   Basic knowledge of database systems, both relational and non-relational, and their query languages (SQL knowledge essential)

•    Advanced knowledge of data modelling and schema design principles

•   Familiarity with data integration and ETL (Extract, Transform, Load) concepts and processes

•   Basic experience with version control systems such as Git

Cloud and Platform Knowledge

•   Basic familiarity with cloud platforms, preferably AWS services such as S3, EC2, and RDS

•    Exposure to big data technologies and frameworks such as Spark or similar platforms

•    Experience with Databricks and implementing batch/real-time data pipelines

Experience:

• 5+ years of experience in data engineering, cloud infrastructure, platform engineering or related technical roles
• Experience with any cloud platform (AWS, Azure, or GCP)
• Knowledge and experience business intelligence tools such as Power BI, AWS QuickSight, or similar platforms
• Experience with data visualisation tools and techniques
• Familiarity with agile development methodologies
• Previous project experience involving data processing or analytics

Special Certification(s):

• Possess any of the certifications would be considered:
• AWS Certified Data Engineer
• Databricks Certified Data Engineer