Senior Data Engineer - Scalable Pipelines & Cloud

Tap Growth ai; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tap Growth ai Senior Data Engineer role based in Singapore focuses on designing, developing, and maintaining scalable data pipelines using Python, SQL, and cloud platforms. You will work with large datasets and modern data technologies to deliver reliable data products.

Requires hands-on experience with ETL/ELT, data modelling, warehouses & lakes, and orchestration tools like Airflow. Collaborative work with Data Architects, Analysts, and Developers is essential.

Qualifications

• Bachelor’s degree in Computer Science, IT, Engineering, or related field.
• 8+ years of experience in Data Engineering or related data role.
• Experience with enterprise-scale data platforms.
• Experience in Agile environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Develop data solutions using Python and SQL.
• Build and optimize data processing and transformation workflows.
• Work with cloud-based data platforms and services.
• Design and maintain data models, data warehouses, and data lakes.
• Support both batch and real-time data processing requirements.
• Implement data quality checks, monitoring, and error handling.
• Optimize data pipelines and queries for performance and reliability.
• Work closely with Data Architects, Analysts, Developers, and other stakeholders.
• Support production issues, troubleshooting, and continuous improvement.

Skills

Python

SQL

ETL/ELT

Data modelling

Data warehousing

Data lakes

AWS

Azure

Apache Spark / PySpark

Airflow

Git & CI/CD

Data governance

Education

Bachelor’s degree in Computer Science / IT / Engineering

Tools

Databricks

Snowflake

Kafka

Terraform

Power BI

Tableau

Azure Data Factory

Job description

Tap Growth ai Senior Data Engineer role based in Singapore focuses on designing, developing, and maintaining scalable data pipelines using Python, SQL, and cloud platforms. You will work with large datasets and modern data technologies to deliver reliable data products.

Requires hands-on experience with ETL/ELT, data modelling, warehouses & lakes, and orchestration tools like Airflow. Collaborative work with Data Architects, Analysts, and Developers is essential.