M16 - Data Engineer, Kallang

Overview 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