Data Engineer with kafka

RAPSYS TECHNOLOGIES PTE LTD; Singapore; On-site; SGD 90,000 - 160,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE LTD is seeking a Data Engineer with Kafka to join our Singapore office. The ideal candidate has at least 4 years of data engineering experience and strong knowledge of real-time streaming to build robust data pipelines for business decisions.

As part of the data platform team, you will design pipelines, validate data quality, monitor data flows, and develop dashboards to drive insights.

Qualifications

• Bachelor's degree or higher in computer science, data science, statistics, or related field.
• 8+ years working in data platform, data analytics, or similar projects.

Responsibilities

• Design and maintain basic data pipelines and integration processes for reliable data flow.
• Implement and monitor data validation and cleansing to improve data quality.
• Support and troubleshoot data pipelines and databases for platform stability.
• Develop dashboards and reports to visualize key metrics for analytics teams.
• Collaborate with stakeholders to gather data requirements and align solutions with business needs.
• Communicate data insights clearly to non-technical stakeholders.
• Analyze structured and unstructured data to identify trends and patterns.

Skills

Kafka

Python

SQL

Data Analytics

BI Tools

Education

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

Tools

Informatica

Kettle

Talend

Airflow

Dolphin

Job description

We're Hiring: Data Engineer with Kafka!

We are looking for a skilled Data Engineer with expertise in Kafka to join our dynamic team. The ideal candidate will have at least 4 years of experience in data engineering, strong knowledge of real-time data streaming, and a passion for building robust data pipelines that empower business decisions.

Location: Singapore, Singapore
Work Mode: Work from Office
Role: Data Engineer with Kafka

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.

CORE COMPETENCY

• Data Analytics
• Design thinking
• Business Needs Analysis
• Data Engineering
• Data Quality Assurance
• Data Security & Compliance