Data Engineer
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- Geospatial Data location_onUnited Kingdom (On-site) schedulePosted today workFull time bar_chartSenior CI/CDData QualityGeoJSONGeoPandasGeospatialGeospatial EngineeringGIS Data PipelinesGitPopulation analysisPythonQGISQuality ChecksShapelySpatial DataSQLUAV Data ProcessingWGS84
About The Role
Data Engineer – Demographic & Geospatial Data
About the Role
We are seeking a hands-on Data Engineer to build Databricks pipelines that combine demographic data with geographic reference data, delivering reliable, reconciled datasets for population analysis and service planning.
Key Responsibilities
Design and deploy pipelines using Databricks, Python, PySpark, SQL and Delta Lake Standardise postcodes and enrich records using NHS and ONS postcode products and ODS reference data Implement spatial joins and point-in-polygon matching, handling edge cases and multiple matches Version lookups and boundaries so historical outputs stay reproducible Automate data quality checks and reconcile counts before and after joins Optimise Spark and spatial processing as data volumes grow Apply access, pseudonymisation and disclosure controls to sensitive data Essential Skills Strong Databricks, Python, PySpark and SQL in production Geospatial engineering: CRS (BNG, WGS84), geometry validation, GeoJSON, WKT/WKB, GeoParquet Apache Sedona or native Databricks spatial functions Git, CI/CD, automated testing and clear communication with analysts Desirable NHS demographic or registration data; LSOAs, MSOAs, ICBs; UPRNs GeoPandas, Shapely or QGIS; regulated data environments domain RiskPod Leading-edge innovations and technical excellence in the geospatial domain.
About The Role
Data Engineer – Demographic & Geospatial Data
About the Role
We are seeking a hands-on Data Engineer to build Databricks pipelines that combine demographic data with geographic reference data, delivering reliable, reconciled datasets for population analysis and service planning.
Key Responsibilities
Design and deploy pipelines using Databricks, Python, PySpark, SQL and Delta Lake Standardise postcodes and enrich records using NHS and ONS postcode products and ODS reference data Implement spatial joins and point-in-polygon matching, handling edge cases and multiple matches Version lookups and boundaries so historical outputs stay reproducible Automate data quality checks and reconcile counts before and after joins Optimise Spark and spatial processing as data volumes grow Apply access, pseudonymisation and disclosure controls to sensitive data Essential Skills Strong Databricks, Python, PySpark and SQL in production Geospatial engineering: CRS (BNG, WGS84), geometry validation, GeoJSON, WKT/WKB, GeoParquet Apache Sedona or native Databricks spatial functions Git, CI/CD, automated testing and clear communication with analysts Desirable NHS demographic or registration data; LSOAs, MSOAs, ICBs; UPRNs GeoPandas, Shapely or QGIS; regulated data environments
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