Senior Data Engineer

VINOVA PTE. LTD.; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading tech company in Singapore is seeking a Senior Data Engineer to mentor and support the data engineering team. This role involves designing data pipelines, ensuring data quality, and collaborating with various teams to meet business data requirements. Candidates should have strong programming skills in Python or Java, knowledge of SQL, and familiarity with data governance practices. The position offers opportunities for professional development and contributions to impactful data initiatives.

Qualifications

• Experience in building and maintaining data pipelines.
• Ability to design data architectures for various source systems.
• Knowledge of data quality and integrity processes.

Responsibilities

• Mentor data engineers and lead technical discussions.
• Assist in designing data pipelines and architectures.
• Implement data validation and monitoring processes.
• Support the maintenance of data infrastructure.
• Collaborate with teams to translate business requirements.

Skills

Proficiency in Python, Java or Scala

SQL knowledge

Data modelling and schema design

Data integration and ETL

Git version control

Familiarity with AWS services

Big data technologies (e.g., Spark)

Databricks experience

Understanding data governance and security

Job description

You will be part of a high-performing and multi-disciplinary research division in NCSS that conducts a range of research initiatives that impacts policy and operations in Singapore’s social service sector. NCSS has multiple operations systems and is currently implementing a new Data Platform where data will be aggregated and transformed to answer strategic business questions.

The Senior Data Engineer will mentor data engineers to build and maintain robust infrastructure and systems across NCSS’ digital ecosystem.

The team will be instrumental in supporting the development of data pipelines and infrastructure that ensure clean, accurate, and timely data is available for business analytics, decision-making, and AI applications.

Guide and plan data engineering processes for NCSS digital systems. Lead technical discussions with the data engineering team and stakeholders to shape the future of NCSS’s digital products. 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.

Data Infrastructure Support

• Assist in designing and developing data pipelines and architectures to collect, process, harmonize and store data from various source systems across NCSS digital products
• Support the building of data pipelines that integrate data from multiple NCSS platforms and services
• Help maintain data lakes and database infrastructure to support analytical, reporting, and AI workloads across the NCSS 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 NCSS 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 across NCSS 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

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
• Understanding of data governance policies, access controls, and security best practices in government environments. Knowledge in data science, statistical analysis and/or machine learning techniques to allow better collaboration with researchers and analysts to support their workflows within the Data Platform ecosystem