As a Quality Engineer you will be supporting and extending workflows for testing and validation purposes. Partner with Data Science teams for the development of geospatial machine‑learning models for advanced quality evaluation in accordance with SD/HD Map specifications.

• 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.

The Sr Quality Engineer will advance the maturity of quality engineering practices by applying spatial data engineering techniques to validate data quality across extraction, transformation, and loading stages using automated geospatial workflows.

• You have 7+ years of experience in geospatial quality testing, spatial data engineering, or related technical roles with bachelor’s degree required in GIS/Geography, Computer Science, Engineering, Data Science, or related fields preferred.
• Strong understanding of SD/HD map databases, geospatial schemas, and location-based data products.
• Machine Learning & AI :Experience applying geospatial machine learning and AI models for classification, anomaly detection, clustering, or automated quality checks is a strong plus.
• Cloud & Architecture :Experience with AWS services, including architecture design, data pipelines, monitoring, and application deployment is advantageous.
  
• Advanced Scripting & Data Engineering : Advanced expertise in Python for automation, spatial libraries, and data engineering workflows and Strong experience with SQL, including relational and spatial databases and performance‑optimized queries.
• Spatial Processing & GIS Tools: Advanced experience with FME, ArcGIS, QGIS, and spatial data transformation workflows.
• Automation & Pipeline Development :Demonstrable experience building robust, automated spatial data pipelines, including QA/QC, feature extraction, integrity checks, and batch processing and Familiarity with geospatial data engineering
• Analytics & Visualization Experience with Tableau, analytics, and building insights dashboards.Strong ability to work with cross-functional analytics teams.Coupling the skills above with strong internal attribute domain knowledge, advanced analytical abilities, and deep understanding of HERE’s product ecosystem is a significant advantage.

What we offer

HERE offers an opportunity to work in a cutting-edge technology environment with challenging problems to solve! You can make a direct impact on delivery of company´s strategic goals and the freedom to decide how to perform your work. We will support you in delivering your day-to-day tasks and achieving your personal goals and developing your skills. Personal development is highly encouraged at HERE. You can take different courses and training at our online Learning Campus and join cross-functional team projects within our Talent Platform.

HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.

This role ensures that HERE’s next generation map products meet rigorous quality standards through robust automation, spatial data engineering practices, and continuous validation innovation. As part of the evolution of our quality testing function, this role builds on attribute specific validation to focus on scalable, automated, data driven geospatial quality workflows