Data Engineer (Geospatial Team)
About the Role
Our Client is seeking a
Data Engineer
to join its Geospatial Team to design, develop, and maintain scalable data platforms that support spatial analytics and long-term infrastructure planning. You will contribute to the development of the Client's Spatial Modelling Engine, which forecasts future education demand using data such as housing growth, demographics, migration patterns, land-use plans, and accessibility. Key Responsibilities
Data Engineering & Solution Design
Collaborate with business users and stakeholders to gather and analyse requirements. Translate business requirements into scalable technical solutions. Design data architecture aligned with data governance and enterprise standards. Data Modelling
Design and implement efficient data models and database structures. Optimise data models for performance, scalability, and maintainability. Work closely with stakeholders to support analytical and reporting requirements. Data Pipeline Development
Design, develop, test, and deploy end-to-end data pipelines. Build data ingestion, transformation, and validation processes. Develop batch and real-time data processing workflows. Implement monitoring, error handling, and data quality checks. Data Platform Operations
Monitor and maintain production data pipelines. Troubleshoot pipeline failures and data quality issues. Optimise system performance and improve platform reliability. Enhance existing data infrastructure through continuous improvement initiatives. Requirements
Minimum Qualifications
Bachelor's Degree in Computer Science, Data Engineering, Information Technology, or a related discipline. Minimum
3-5 years
of experience in Data Engineering, Data Analytics, or a related field. Proven experience designing and implementing enterprise data pipelines. Required Technical Skills
Programming Python SQL pandas NumPy Data Engineering Data ingestion ETL/ELT development Data transformation Data quality management Pipeline orchestration Metadata management Data governance Data lineage Data Architecture Data Lake Data Warehouse Data Lakehouse Data Mesh Preferred Skills
Databricks AWS Cloud Services Cloud data processing and storage solutions Infrastructure-as-Code (Terraform, CloudFormation, or equivalent) DevOps practices for data platforms Advantageous Skills
Experience with one or more of the following: ArcGIS GIS platforms Geospatial APIs Routing engines 2D/3D mapping technologies Soft Skills
Strong analytical and problem-solving skills Excellent communication and stakeholder management skills Ability to work collaboratively with technical and business teams Ability to translate business requirements into technical solutions Strong troubleshooting and performance optimisation capabilities What We're Looking For
The ideal candidate will have: 3-5 years of Data Engineering experience Strong Python and SQL skills Experience building scalable data pipelines Knowledge of modern data architectures Experience with cloud-based data platforms A passion for solving complex data and geospatial challenges
Our Client is seeking a
Data Engineer
to join its Geospatial Team to design, develop, and maintain scalable data platforms that support spatial analytics and long-term infrastructure planning. You will contribute to the development of the Client's Spatial Modelling Engine, which forecasts future education demand using data such as housing growth, demographics, migration patterns, land-use plans, and accessibility. Key Responsibilities
Data Engineering & Solution Design
Collaborate with business users and stakeholders to gather and analyse requirements. Translate business requirements into scalable technical solutions. Design data architecture aligned with data governance and enterprise standards. Data Modelling
Design and implement efficient data models and database structures. Optimise data models for performance, scalability, and maintainability. Work closely with stakeholders to support analytical and reporting requirements. Data Pipeline Development
Design, develop, test, and deploy end-to-end data pipelines. Build data ingestion, transformation, and validation processes. Develop batch and real-time data processing workflows. Implement monitoring, error handling, and data quality checks. Data Platform Operations
Monitor and maintain production data pipelines. Troubleshoot pipeline failures and data quality issues. Optimise system performance and improve platform reliability. Enhance existing data infrastructure through continuous improvement initiatives. Requirements
Minimum Qualifications
Bachelor's Degree in Computer Science, Data Engineering, Information Technology, or a related discipline. Minimum
3-5 years
of experience in Data Engineering, Data Analytics, or a related field. Proven experience designing and implementing enterprise data pipelines. Required Technical Skills
Programming Python SQL pandas NumPy Data Engineering Data ingestion ETL/ELT development Data transformation Data quality management Pipeline orchestration Metadata management Data governance Data lineage Data Architecture Data Lake Data Warehouse Data Lakehouse Data Mesh Preferred Skills
Databricks AWS Cloud Services Cloud data processing and storage solutions Infrastructure-as-Code (Terraform, CloudFormation, or equivalent) DevOps practices for data platforms Advantageous Skills
Experience with one or more of the following: ArcGIS GIS platforms Geospatial APIs Routing engines 2D/3D mapping technologies Soft Skills
Strong analytical and problem-solving skills Excellent communication and stakeholder management skills Ability to work collaboratively with technical and business teams Ability to translate business requirements into technical solutions Strong troubleshooting and performance optimisation capabilities What We're Looking For
The ideal candidate will have: 3-5 years of Data Engineering experience Strong Python and SQL skills Experience building scalable data pipelines Knowledge of modern data architectures Experience with cloud-based data platforms A passion for solving complex data and geospatial challenges