Data Engineer

NEUTRON PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading tech company in Singapore is seeking a Data Engineer to support cloud data infrastructure initiatives. Responsibilities include leading migration efforts, developing data pipelines, and ensuring data quality. The ideal candidate will have a Bachelor’s degree in a relevant field, with 1-3 years of experience in data engineering and familiarity with AWS platforms. Strong proficiency in Python, SQL, and BI tools like Tableau is essential. Join us to drive innovative data solutions in a collaborative environment.

Qualifications

• 1-3+ years of experience in data engineering or cloud infrastructure.
• Experience with data visualization and development of data pipelines.
• Relevant certifications such as AWS Certified Data Engineer are advantageous.

Responsibilities

• Lead migration of on-premises and legacy systems to cloud platforms.
• Develop and maintain data infrastructure and pipelines.
• Collaborate with teams to ensure data integrity and access.

Skills

Proficiency in Python

SQL knowledge

Experience with AWS services (S3, Lambda, etc.)

Familiarity with big data frameworks (Spark, Databricks)

Experience with BI tools (Tableau, Power BI)

Version control (Git)

Strong communication skills

Education

Bachelor’s degree in Computer Science or related field

Tools

Databricks

AWS

Tableau

Power BI

Job description

About the Role

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. You will be involved 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

Migration & Technical Implementation

• Lead migration of on-premises and SharePoint/legacy systems to our cloud-based data platform.
• Collaborate with cloud engineering teams to develop migration strategies and implementation plans.
• Re-architect existing Python scripts and UiPath automation workflows for cloud-native services.
• Design and implement scalable ETL/ELT pipelines and data integration workflows.
• Migrate Tableau dashboards to modern BI platforms such as QuickSight, ensuring full functionality.
• Establish data connections from multiple enterprise systems.
• Ensure seamless transition with minimal disruption.

Data Infrastructure & Architecture

• Guide and plan data engineering processes across digital systems.
• Develop and maintain data lakes, warehouses, and database infrastructure.
• Define data architecture standards and DevOps best practices.
• Support the development of pipelines integrating data from multiple platforms.

Data Quality & Governance

• Implement data validation, cleansing, and harmonisation processes to ensure integrity.
• Monitor pipelines for issues and performance bottlenecks.
• Support data governance, access control, and compliance needs.

System Maintenance & Documentation

• Maintain cloud and on-prem data infrastructure.
• Troubleshoot and resolve data-related issues.
• Create and maintain documentation for engineering processes.

Stakeholder Collaboration

• Work with product teams, analysts, and stakeholders to translate business requirements.
• Develop and deploy data tables, marts, and visualisation layers for reporting.
• Support users in accessing analytics dashboards.

Training & Knowledge Transfer

• Mentor and train junior engineers.
• Conduct knowledge-sharing sessions.
• Prepare training materials for new systems.

Innovation & Continuous Improvement

• Stay updated with emerging technologies and contribute to process enhancements.
• Participate in continuous learning and internal capability development.

Skills & Knowledge

• Proficiency in Python, and familiarity with Java or Scala.
• Strong knowledge of SQL, data modelling, schema design, and ETL/ELT processes.
• Experience with AWS services such as S3, Lambda, Glue, SageMaker, Athena, RDS, QuickSight.
• Familiarity with big data and analytics frameworks (e.g., Spark, Databricks).
• Experience with version control (Git) and DevOps pipelines (GitLab, CI/CD, Nexus).
• Understanding serverless architectures and Infrastructure-as-Code (CloudFormation, YAML/JSON).
• Knowledge of data governance, security best practices, and enterprise access controls.
• Experience with BI tools such as Tableau, Power BI, or QuickSight.
• Strong communication, analytical thinking, and stakeholder management skills.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, IT, or related field.
• 1-3+ years of experience in data engineering, cloud infrastructure, or platform engineering.
• Experience with cloud platforms (preferably AWS) and data pipeline development.
• Experience with data visualisation and business intelligence tools.
• Extensive experience in Databricks and AWS experience.
• Familiarity with agile development methodologies.
• Relevant certifications such as AWS Certified Data Engineer or Databricks Certified Data Engineer are advantageous.