Data Engineer with kafka

Tap Growth ai; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Tap Growth ai in Singapore is hiring a Data Engineer with Kafka to build robust real-time data pipelines and empower business decisions.

The role requires 4+ years of data engineering experience, strong Python/SQL skills, and familiarity with cloud platforms and BI tools. Work from the office in Singapore with close collaboration across teams.

Qualifications

• Bachelor's degree in CS/Data Science/Statistics or related field.
• 4+ years of experience in data platform, data analytics or relevant projects.
• Proven experience as a Data Engineer with design/manage enterprise data architecture (batch and real-time).
• Strong programming skills in Python and SQL; experience with data models, ETL and data integration.

Responsibilities

• 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.
• Support and troubleshoot operational issues in data pipelines and databases to maintain platform performance.
• Develop and update dashboards and reports to visualize key metrics for data-driven decisions.
• Collaborate with stakeholders to gather data requirements and ensure solutions meet business needs.
• Communicate data insights clearly to non-technical stakeholders.
• Assist in analyzing structured and unstructured data to identify trends.

Skills

Kafka

Python

SQL

Real-time data streaming

Communication

Education

Bachelor's degree

Tools

Airflow

Informatica

Talend

Databricks

Snowflake

Azure Data Factory

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