Data Engineer with kafka

Rapsys Technologies Pte Ltd.; Singapore; Presencial; SGD 90 000 - 130 000; Tempo integral

Resumo da oferta

Rapsys Technologies Pte Ltd. is hiring a Data Engineer with Kafka in Singapore. The role focuses on building robust data pipelines, real-time streaming, and scalable data architectures to empower business decisions.

Ideal candidates will have 4+ years of data engineering experience, strong SQL/Python skills, and hands-on knowledge of cloud data platforms and BI tools. The position is office-based in Singapore with a collaborative team environment.

Qualificações

• Experience in data platform, data analytics or relevant projects.
• Proven experience designing and managing enterprise data architecture, including batch and real-time processing.
• Strong programming skills in Python, SQL, SAS, or R for data analysis and data engineering tasks.
• Experience with data models, ETL processes, and data integration solutions.
• Experience with at least one major data processing tool (Informatica, Kettle, Talend, Airflow, Dolphin, etc.).
• Experience with cloud-based data platforms (Azure Data Factory, Azure Purview, Databricks, Snowflake, Kafka, etc.) and data storage tech (SQL/NoSQL, Vector and Graph).
• Excellent problem-solving skills and ability to work with large data sets.
• Effective communication to convey complex concepts to non-technical stakeholders.
• Ability to work independently and in a team, in a fast-paced environment.
• Experience with AI tech stack is a plus.
• Experience with BI tools (Power BI, Tableau).
• Related industry experience is a plus.

Responsabilidades

• Data Engineering & Platform Support.
• Design and maintain basic data pipelines and integration processes to support reliable data flow and analytics.
• Implement and monitor data validation and cleansing routines to improve data quality and reporting accuracy.
• Support and troubleshoot operational issues in data pipelines and databases for smooth performance.
• Develop and update dashboards and reports to visualize key metrics and support data-driven decisions across teams.
• Collaboration with stakeholders to gather data requirements and ensure solutions align with business needs.
• Communicate data insights to non-technical stakeholders.
• Assist in analyzing structured and unstructured data to identify trends.
• Learning and applying suitable ML models under guidance to support business use cases.

Conhecimentos

Data engineering

Real-time streaming

Python

SQL

ETL

Data modeling

Problem-solving

Communication

Formação académica

Bachelor's degree in Computer Science, Data Science, Statistics, or a related field

Ferramentas

Kafka

Airflow

Azure Data Factory

Databricks

Snowflake

Power BI

Tableau

Descrição da oferta de emprego

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 Responsibilities (Job Requirements)

• 1 Data Engineering & Platform Support
• 2 Design and maintain basic data pipelines and integration processes to support reliable data flow and ensure data availability for analytics.
• 3 Implement and monitor data validation and cleansing routines to improve data quality and ensure accurate reporting.
• 4 Support and troubleshoot operational issues in data pipelines and databases to maintain smooth and continuous platform performance.
• 5 Develop and update dashboards and reports to visualize key metrics and support data-driven decision-making across teams.

• 1 Collaboration & Business Understanding
• 2 Collaborate with stakeholders to gather data requirements and ensure solutions align with business needs and objectives.
• 3 Communicate data insights and findings in a clear and actionable manner to support informed decision-making by non-technical stakeholders.
• 4 Assist in analyzing structured and unstructured data to identify trends and patterns that contribute to solving business problems.

• 1 Learning & Continuous Improvement
• 2 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