Sr Quality Engineer (SD/HD map, Spatial Data Engineering)
HERE Technologies View all jobs
- Mumbai, Maharashtra
- Permanent
- Full-time
- Technical Subject Matter Expert (SME) for spatial data models and automated geospatial quality-testing methodologies adhering to SD/HD map specifications
- Plan, schedule, and oversee automated data annotation, spatial integrity checks, and validation tasks aligned with Product Testing frameworks and evolving testing requirements.
- Implement, and optimize automated QA pipelines using geospatial processing frameworks.
- Integrating machine learning–powered validation signals by collaborating with Data Science to integrate outputs from spatial ML models for anomaly detection, classification, feature validation, and predictive quality scoring.
- Integrate and validate API d-riven ingestion processes within the quality framework including JSON/XML parsing, schema validation, and automated integration with internal and external data sources.
- Lead continuous improvement efforts of system inefficiencies via root cause- analyses, and engineering enhancement to improve automation efficiency in testing workflows.
- Develop, document, and enforce technical testing procedures, ensuring consistency, repeatability, and compliance across global teams and distributed test environments.
- Provide technical training and mentorship to internal and external contributors on advanced scripting, automation tools, geospatial processing techniques, and cloud based validation workflows.
- Bachelor’s degree required; GIS/Geography, Computer Science, Engineering, Data Science, or related fields preferred.
- 7+ years of experience in geospatial quality testing, spatial data engineering, or related technical roles.
- Strong understanding of SD/HD map databases, geospatial schemas, and location-based data products
- Experience applying geospatial machine learning and AI models for classification, anomaly detection, clustering, or automated quality checks is a strong plus.
- Experience with AWS services, including architecture design, data pipelines, monitoring, and application deployment is advantageous.
- Advanced proficiency in Python, including automation scripting, spatial libraries, and data engineering workflows.
- Strong experience with SQL, relational databases, spatial SQL, and performance optimized spatial queries.
- Proficiency in API based data extraction, JSON/XML parsing, and integrating external data sources into automated pipelines.
- Advanced experience with FME, ArcGIS, QGIS, and spatial data transformation workflows.
- Demonstrable experience building robust, automated spatial data pipelines, including QA/QC, feature extraction, integrity checks, and batch processing.
- Experience with Tableau, analytics, and building insights dashboards.