Sr. Data Engineer

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

We're Hiring: Sr. Data Engineer!

We are seeking an experienced Senior Data Engineer to design, develop, and maintain scalable data solutions and pipelines in an enterprise environment. The ideal candidate will have strong hands-on experience in Python, SQL, cloud platforms, data pipelines, and modern data technologies, with the ability to work with large and complex datasets.

Key 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.

General Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• 8+ years of experience in Data Engineering or a related data role.
• Strong experience working with enterprise-scale data platforms and applications.
• Experience working in Agile and collaborative technical environments.

Mandatory Skills

• Strong hands-on experience with Python.
• Strong SQL skills, including query optimization and data manipulation.
• Experience developing ETL/ELT data pipelines.
• Experience with data modelling, data warehousing, and data lakes.
• Hands-on experience with AWS or Azure.
• Experience with Apache Spark / PySpark or similar distributed data processing technologies.
• Experience with data orchestration tools such as Airflow, Azure Data Factory, or equivalent.
• Experience with Git and CI/CD.
• Good understanding of data quality, security, and governance.

Nice-to-Have Skills

• Experience with Databricks or Snowflake.
• Experience with Kafka or other streaming technologies.
• Experience with Terraform or Infrastructure as Code.
• Experience with Power BI, Tableau, or other analytics platforms.
• Cloud or Data Engineering certifications.
• Experience in banking, financial services, or other large enterprise environments.