Data Engineer

RAPSYS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE. LTD. in Singapore is seeking a Data Engineer to design and maintain data pipelines, ensure data quality, and develop dashboards for analytics. You will collaborate with stakeholders to gather data requirements and translate insights to non-technical teams.

The role emphasizes learning, continuous improvement, and applying ML techniques under guidance, with a focus on reliable data platforms and scalable solutions.

Qualifications

• Bachelor's degree in CS/DS/stats or related field.
• Experience in data platform, data analytics or relevant projects.
• Proven Data Engineer with batch and real-time processing design & management.
• Proficient in Python/SQL/SAS/R for data tasks.
• Experience with ETL tools (Informatica, Kettle, Talend, Airflow, Dolphin).
• Cloud data platforms (Azure Data Factory, Purview, Databricks, Snowflake, Kafka).
• Strong problem-solving and attention to detail.
• Excellent communication for non-technical stakeholders.
• Ability to work independently and in a fast-paced team.
• AI tech stack experience is a plus.
• Experience with BI tools (Power BI, Tableau).
• Related industry experience is a plus.

Responsibilities

• Design and maintain data pipelines and integration processes for analytics.
• Implement data validation and cleansing routines to ensure data quality.
• Troubleshoot data pipelines and databases for platform stability.
• Develop dashboards and reports to visualize key metrics.
• Collaborate with stakeholders to gather data requirements.
• Communicate insights to non-technical stakeholders.
• Analyze structured and unstructured data to identify trends.
• Research ML models under guidance to support business use cases.
• Stay updated on data engineering and analytics trends and tools.
• Suggest improvements to increase data pipeline efficiency and reliability.

Skills

Data engineering

Data analytics

Communication

Problem solving

Independent & team work

Learning mindset

Attention to detail

Education

Bachelor's degree in CS/DS/Statistics

Tools

Python

SQL

SAS

R

Informatica

Airflow

Talend

Azure Data Factory

Databricks

Snowflake

Power BI

Tableau

NoSQL

Job description

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.
• 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.

CORE COMPETENCY

1. Data Analytics
2. Design thinking
3. Business Needs Analysis
4. Data Engineering
5. Data Quality Assurance
6. Data Security & Compliance