Senior Data Engineer (Databricks, Power BI)

CMC-APAC PRIVATE LIMITED; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

CMC-APAC PRIVATE LIMITED is seeking a Senior Data Engineer to lead data engineering across the organisation's digital platform in Singapore. You will mentor engineers, shape data pipelines, and ensure data quality for analytics and AI applications.

The role emphasizes architectural leadership, collaboration with product teams, and governance to support strategic decisions with timely data.

Qualifications

• Bachelor's degree in a technical field is required.

Responsibilities

• Provide data engineering leadership and set data engineering standards.

Skills

Python/Java/Scala

SQL

Data modelling

ETL concepts

Git

Cloud platforms

Databricks/Spark

Data governance

ML collaboration

Education

Bachelor's Degree in Computer Science / Data Science / Engineering

Tools

Databricks

Power BI

AWS QuickSight

Git

Job description

Job Purpose / Job Summary

You will be part of a high-performing and multi-disciplinary research division that conducts a range of research initiatives that impacts policy and operations in Singapore’s social service sector. Our client 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 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.

Key Responsibilities and Activities

Data Engineering Leadership

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

Mentor and Train the Data Engineering Team

Data Infrastructure Support

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

Behaviors Needed to Succeed

Personal Competencies

• Self-driven and takes the initiative
• Analytical and critical thinker
• Strong project management
• Excellent communication and stakeholder management skills

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.

Requirements

Education

• A Bachelor's Degree in Computer Science, Data Science, Engineering, Information Technology, or related technical field.

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 in 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.

Preferred Certifications

Possess any of the certifications below would be considered:

• AWS Certified Data Engineer
• Databricks Certified Data Engineer