M16 - Data Engineer

FPT Asia Pacific; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

FPT Asia Pacific in Singapore seeks a Data Engineer to design and maintain scalable pipelines and data platforms for data-driven applications and analytics.

You will build data warehouses, data lakes, and real-time pipelines with GIS-focused capabilities, collaborating with cross-functional teams in an Agile environment. 4+ years of experience and cloud expertise are required.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• Minimum 4 years of experience in data engineering, data platform development, or related roles.
• Strong experience in data engineering and pipeline development.
• Proficiency in databases, SQL, and data processing frameworks.
• Experience with cloud data platforms.
• Familiarity with Agile and CI/CD practices.
• Familiar with GIS platforms: ArcGIS Server, PostGIS.
• Able to use spatial Python libraries: GeoPandas, Shapely.
• Build scalable geospatial data pipelines for ingestion, transformation, storage, and quality checks from multiple government sources.
• Implements data cataloging, metadata, lineage, and security; optimizes storage and performance for GIS analytics (e.g., PostGIS, data lakes).
• Provides reliable data services and contracts to support downstream GIS analytics and front-end visualizations, collaborating closely with GIS and frontend teams.
• Data management: applies validation, cleansing, reprojection, metadata, and data lineage of geospatial data

Responsibilities

• Build and maintain scalable data pipelines and platforms for data-driven applications and analytics.
• Design, develop and deploy data tables, views and marts in data warehouses, data lake and virtualization.
• Perform data extraction, cleaning, transformation, and flow.
• Design, build and maintain large-scale batch and real-time data pipelines with processing frameworks.
• Integrate and collate data silos in a scalable and compliant manner.
• Collaborate with Product Manager, Data Architect, BAs, Frontend Devs and Data Analysts to build scalable data-driven products.
• Develop backend APIs and work on databases to support applications.
• Work in an Agile environment with CI/CD and code reviews.

Skills

Data pipeline design

SQL

Cloud platforms

CI/CD

GIS analytics

Geospatial data

Education

Bachelor's degree in CS/IS/Eng

Tools

ArcGIS Server

PostGIS

GeoPandas

Shapely

Job description

• Build and maintain scalable data pipelines and platforms to support data-driven applications and analytics.

Key Responsibilities

• Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.
• Perform data extraction, cleaning, transformation, and flow.
• Design, build, launch and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks.
• Integrate and collate data silos in a manner which is both scalable and compliant
• Collaborate with Product Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analyst to build scalable data-driven products.
• Be responsible for developing backend APIs & working on databases to support the applications.
• Work in an Agile Environment that practices Continuous Integration and Delivery.
• Work closely with fellow developers through pair programming and code review process.

Key Requirements

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
• Minimum 4 years of experience in data engineering, data platform development, or related roles
• Strong experience in data engineering and pipeline development
• Proficiency in databases, SQL, and data processing frameworks
• Experience with cloud data platforms
• Familiarity with Agile and CI/CD practices
• Familiar with GIS platforms: ArcGIS Server, PostGIS
• Able to use spatial Python libraries: GeoPandas, Shapely
• Build scalable geospatial data pipelines for ingestion, transformation, storage, and quality checks from multiple government sources.
• Implements data cataloging, metadata, lineage, and security; optimizes storage and performance for GIS analytics (e.g., PostGIS, data lakes).
• Provides reliable data services and contracts to support downstream GIS analytics and front-end visualizations, collaborating closely with GIS and frontend teams.
• Data management: applies validation, cleansing, reprojection, metadata, and data lineage of geospatial data