Data Compliance Engineer

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Responsibilities:

Purpose:
The Remote Sensing Data Quality Assurance Analyst ensures the accuracy, consistency, and reliability of LiDAR datasets used in geospatial analysis and decision-making. This role focuses on developing and applying Quality Analyses (QA)/Quality Check (QC) protocols to validate LiDAR point clouds, derived products, and metadata against project specifications and operational standards. The analyst works closely with data engineers, geospatial data analysts, field teams, and Geographic Information Systems specialists to detect and resolve data anomalies, document quality processes, and provide actionable insights that improve LiDAR workflows, modeling accuracy, and end-user confidence.

️ Roles and Responsibilities:

Project Execution:

- Data acquisition, coordination, quality assurance of the data before deploying to the production server.
- Close coordination with potential customers, incorporating feedback and requisite deliverables.

Database Management:

- Running QA tests (Density, Accuracy, Nomenclature, Landuse, Coverage) on all LiDAR data from different applications.
- Root cause analysis and action plan in coordination with field customer and field crew to ensure IOP targets.
- Data transfer and compilation in the storage server.
- Deployment of data in the production server for all Forest Inventory, Microplanning, and Tree improvement applications.
- Collaborate with other divisions to ensure data accuracy and reliability.
- Continuous optimization of the dataset lifecycle policy, curation workflow.
- Develop/build and manage spatial databases linking with other organizational database management systems and create channels for user interaction.
- Support the development of processes for efficient & effective QA/QC of remote sensing data (LiDAR + Optical).
- Day-to-day data curation activities, processing, tracking, validation, and resolution of data quality issues.

Coordinating & Reporting:

- Manage subordinates effectively and ensure project progress.
- Provide suggestions to the remote sensing manager for new ideas and implementations.
- Provide routine reports and operational recommendations to the remote sensing manager regarding project progress and challenges faced.
- Prepare technical reports or presentations on the results of developmental projects.
- Develop standard operational procedures to guide the operational implementation of remote sensing workflows.

 Qualifications:

- Preferably, Masters in Computer Science, Geoinformation Science, or closely related discipline.
- OR Bachelor Degree with some exposure in Data Science.

 Experience:

- Previous quality assessment experience preferably at a management level; proven track record of delivering quality solutions.
- Proven experience with modern quality improvement tools – SPC, capability studies, root cause analysis (fishbone, why-why analysis etc.).
- Experienced in geospatial data validation & calibration procedure, Automated quality control algorithms, quality metadata & documentation.
- Experience in big data management with demonstrated skills in processing, automation, compilation/integration, and deployment in the processing/production server.
- Knowledge about remote sensing, GIS technologies, software & tools and development of datasets & documentation of Earth science data.
- Proficiency with interpreted data languages for Earth science data using either Python, MATLAB, R, IDL, JavaScript etc.
- Six Sigma/LEAN processing certified preferred but not required.
- Competency in project development & deployment strategy.
- Building cross-functional relationships to collaborate with business stakeholders and internal stakeholders/customers.
- Excellent communication, interpersonal and presentation skills. Able to relate technical information to all levels of the organization.

 Specific Knowledge:

- Awareness of market trends and innovations in UAV, Satellite & LiDAR technologies.
- Proficient in statistical & spatial analytics for informed business decisions.
- Understanding of remote sensing data structure and applications in various disciplines.
- Knowledge of artificial intelligence, deep/machine learning methods applicable to remote sensing.
- LiDAR & optical data structure, spatial database management & processing.
- Compilation & integration of model scripts, geospatial applications.
- Expert in geospatial data processing & automation using different programming languages as well as GIS applications.

Disclaimer:

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Only shortlisted candidates will be contacted for an interview. We endeavour to respond to every applicant. However, if you do not receive a response from us within 60 days, please consider your application for this position unsuccessful. We may contact you in the future for any opportunities that match your qualifications and experience.

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Thank you for considering a career with RGE.
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