Data Engineer

RAPSYS TECHNOLOGIES PTE LTD; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE LTD in Singapore seeks an experienced Data Engineer to design, build and maintain scalable data pipelines for insights and innovation. You will work across data architecture, integration, and analytics, collaborating with stakeholders to meet business needs.

The ideal candidate has 8+ years in data platforms, strong Python/SQL skills, and hands-on experience with batch and real-time processing, cloud data services, and BI dashboards.

Qualifications

• Bachelor's degree or higher in a related field.
• 8+ years of experience in data platform and analytics projects.
• Proven data engineering experience with batch and real-time processing.
• Strong programming skills in Python and SQL.

Responsibilities

• Design, build and maintain scalable data pipelines for analytics.
• Implement data validation and cleansing to improve quality.
• Troubleshoot operational issues in data pipelines and databases.
• Develop dashboards and reports to visualize key metrics.
• Collaborate with stakeholders to gather data requirements and insights.
• Apply machine learning techniques under guidance to support use cases.
• Stay updated on data engineering trends and tools to drive improvement.

Skills

Data engineering

Python

SQL

Data modeling

Problem solving

Communication

Education

Bachelor's degree in Computer Science / Data Science / Statistics

Tools

Informatica

Airflow

Azure Data Factory

Databricks

Snowflake

Job description

We are looking for an experienced and driven Data Engineer to join our dynamic team in Singapore. As a key member, you will design, build, and maintain scalable data pipelines that empower business insights and innovation. If you have a passion for data architecture and thrive in collaborative environments, we want to hear from you!

What You’ll Do:KEY RESPONSIBILITES (JOB REQUIREMENTS)

• Data Engineering & Platform Support
• Design and maintain basic data pipelines and integration processes to support reliable data flow and ensure data availability for analytics.
• Implement and monitor data validation and cleansing routines to improve data quality and ensure accurate reporting.
• Support and troubleshoot operational issues in data pipelines and databases to maintain smooth and continuous platform performance.
• Develop and update dashboards and reports to visualize key metrics and support data-driven decision-making across teams.
• Collaboration & Business Understanding
• Collaborate with stakeholders to gather data requirements and ensure solutions align with business needs and objectives.
• Communicate data insights and findings in a clear and actionable manner to support informed decision-making by non-technical stakeholders.
• Assist in analyzing structured and unstructured data to identify trends and patterns that contribute to solving business problems.
• Learning & Continuous Improvement
• Research and apply suitable machine learning models or statistical techniques under guidance to support business use cases.
• Stay updated on industry trends and tools in data engineering and analytics to enhance technical skills and contribute to team innovation.
• Recommend and support process improvements to increase data pipeline efficiency and improve data reliability over time.

JOB REQUIREMENTS/JOB QUALIFICATIONS

• Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.
• At least 8 years’ working experience in data platform, data analytics or relevant projects.
• Proven experience as a Data Engineer, with design and managing enterprise data architecture, including batch and real time processing.
• Solid programming skills in languages such as Python, SQL, SAS, or R for data analysis and data engineering tasks.
• Prior experience as a Data Engineer, with a demonstrated ability to design and implement data models, ETL processes, and data integration solutions.
• Proven experience in at least one major data processing tool (Informatica, Kettle, Talend, Airflow, Dolphin etc.).
• Prior experience with cloud-based data platforms (e.g., Azure Data Factory, Azure Purview, Databricks, Snowflake, Kafka, or equivalent) and data storage technologies (e.g., SQL/NoSQL, Vector and Graph etc.).
• Excellent problem-solving skills and the ability to work with large, complex data sets.
• Strong attention to detail, ensuring data accuracy and reliability in all analyses.
• Effective communication skills to convey complex technical concepts to non-technical stakeholders.
• Proven ability to work independently as well as collaboratively in a fast-paced, team-oriented environment.
• Prior experience of AI technology stack is a great plus.
• Prior experience in at least one BI tool (Power BI, Tableau, etc.).
• Related industry experience is a plus.

Keen to drive innovation through data? and be part of our growth journey!