Geographic Information Systems Engineer

Core Skills: Spatial/GIS with ARCGIS, QGIS, PostGreSQL, PostGIS with Masters in GIS with specialization for each Job Type. ROLE 1:Spatial Data Engineer (ETL + Quality Focus)Role Summary: Design, enhance, and operate scalable spatial ETL pipelines ensuring high-quality geospatial data ingestion, validation, and transformation. Key ResponsibilitiesBuild and optimize ETL pipelines for spatial datasets (vector, raster, LiDAR metadata)Integrate new data sources into existing pipelines (APIs, files, DBs)Develop data validation frameworks (schema, topology, geometry checks)Perform RCA for data quality issues and pipeline failuresAutomate ingestion workflows using FME / Python / SQLOptimize pipeline performance (latency, cost, scalability)Implement data quality KPIs and monitoring dashboardsTech StackGIS: QGIS / ArcGISDB: PostgreSQL + PostGISETL: FME, PythonQuery: SQL, Trino (nice to have) ROLE 2:GIS Data Analyst / Investigation Analyst (Capture Team)Role Summary: Analyze, investigate, and validate map data issues (HVSLI) and support data capture workflows with high attention to detail. Key ResponsibilitiesPerform HVSLI investigations (map discrepancies, missing attributes)Analyze spatial data using ArcGIS + SQL queriesDocument findings and maintain QC reports and audit trailsSupport data upload workflows and correctionsCollaborate with engineering teams to resolve data issuesValidate incoming datasets against defined standardsTech StackGIS: ArcGISQuery: SQLScripting: Python (basic)Optional: APIs, AWS ROLE 3:GIS QA/QC Engineer (SLI Validation Specialist)Role Summary: Ensure end-to-end quality validation of map features (FC5, SLI) across markets through systematic testing and benchmarking.Key ResponsibilitiesPerform SLI validation for map features (lanes, roads, attributes)Execute test cases for FC5 and new attribute rolloutsBenchmark datasets across geographies and releasesDevelop and execute QC routines and validation scriptsSupport OEM programs with quality certificationIdentify defects and drive RCA + defect closureTech StackGIS: ArcGIS, QGISScripting: PythonETL/QC: FMEDB: SQL ROLE 4:Senior Spatial Data Engineer (Platform + Automation + AI)Role Summary: Design and build next-gen automated spatial data pipelines with strong focus on scalability, observability, and AI-driven enhancements.Key ResponsibilitiesArchitect end-to-end data pipelines (batch + near real-time)Integrate multi-source data (PostGIS, Oracle, APIs, geodatabases)Implement data validation, monitoring, and observability frameworksBuild reusable components and data engineering best practicesDrive CI/CD, code quality, and version control (Git)Automate bulk updates, transformations, and conversionsLeverage AI/ML (VLMs) for pre-validation / enrichmentOwn pipeline performance, reliability, and cost optimization Tech StackGIS: QGISDB: PostGIS, OracleLanguages: Python, SQLTools: FME, Git, CI/CDAI: VLM exposure (nice to have)

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