Senior Data Engineer, Upto $12k

Ambition; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Ambition is seeking a Senior Data Engineer to join our Data & Analytics team to help build scalable, enterprise-grade data platforms. You will design and maintain ETL/ELT pipelines, implement lakehouse architectures, and enable data-driven decision-making across the organization.

You will work with Python, PySpark, SQL Server, Kubernetes, and Docker, implement CI/CD, ensure data governance, and collaborate with cross-functional teams to deliver trusted data solutions.

Qualifications

• 5+ years of hands-on data engineering experience.
• Strong expertise in SQL Server, performance tuning.
• Advanced Python programming with PySpark experience.
• Experience with Kubernetes, Docker, and modern DevOps practices.
• Knowledge of data modeling, lakehouse architectures, and Iceberg.
• Experience with Airflow for workflow orchestration.
• Hands-on NoSQL experience (MongoDB/Cassandra).
• Understanding of data security, governance, and access control.

Responsibilities

• Design, build, and maintain ETL/ELT data pipelines using Python and PySpark.
• Develop lakehouse/data lake architectures, including data modeling and metadata management.
• Deploy and support containerized data solutions using Kubernetes and Docker.
• Optimize SQL Server databases and data models for performance.
• Implement CI/CD, automated testing, and monitoring for data platforms.
• Ensure data governance, security, and compliance standards.
• Collaborate with cross-functional teams to deliver scalable data solutions.
• Provide technical guidance and code reviews for continuous improvement.

Skills

Python

PySpark

SQL Server

Kubernetes

Docker

Apache Airflow

Data Modeling

Lakehouse

Apache Iceberg

NoSQL (MongoDB/Cassandra)

Education

Bachelor's degree in Computer Science/IT/Engineering

Tools

Kubernetes

Docker

Apache Airflow

MongoDB

Cassandra

Apache Iceberg

Job description

We are looking for an experienced Senior Data Engineer to join a Data & Analytics team and contribute to the development of scalable, enterprise-grade data platforms. This role will focus on designing and maintaining data pipelines, implementing modern lakehouse solutions, and enabling data-driven decision-making across the organization.

Key Responsibilities

• Design, build, and maintain ETL/ELT data pipelines using Python and PySpark.
• Develop and manage lakehouse/data lake architectures, including data modeling, partitioning, and metadata management.
• Deploy and support containerized data solutions using Kubernetes and Docker.
• Optimize SQL Server databases, data models, and query performance.
• Implement CI/CD practices, automated testing, and monitoring for data platforms.
• Ensure data governance, security, and compliance standards are met.
• Collaborate with cross-functional teams to deliver trusted and scalable data solutions.
• Provide technical guidance, perform code reviews, and support continuous improvement initiatives.

Requirements

• At least 5 years of hands-on experience in data engineering, ETL/ELT development, or related fields.
• Strong expertise in SQL Server, including performance tuning and optimization.
• Advanced Python programming skills and experience with PySpark.
• Experience with Kubernetes, Docker, and modern DevOps practices.
• Knowledge of data modeling, lakehouse/data lake architectures, and Apache Iceberg.
• Experience with workflow orchestration tools such as Apache Airflow.
• Hands-on experience with NoSQL databases (e.g., MongoDB, Cassandra).
• Understanding of data security, governance, and access control principles.
• Strong analytical, problem-solving, and stakeholder management skills.
• Degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience.

Short listed candidates will be notified

EA Registration Number: R22106307

Business Registration Number: 200611680D. License Number: 10C5117