Data Compliance Engineer

6923 Sateri (Nantong) Fiber Co., Ltd.; Kecamatan Pangkalan Kerinci; On-site; IDR 180,000,000 - 300,000,000; Full time

Job summary

6923 Sateri (Nantong) Fiber Co., Ltd. is seeking a Remote Sensing Data Quality Assurance Analyst to ensure LiDAR data accuracy and reliability. You will develop QA/QC protocols, validate datasets, and work with data engineers, GIS specialists and field teams to improve workflows and decision-making.

Responsibilities include running QA tests, documenting quality processes, and delivering actionable insights to enhance LiDAR performance and end-user confidence.

Qualifications

• Masters in Computer Science or Geoinformation Science or related field.
• Bachelor degree with exposure to Data Science.

Responsibilities

• Ensure accuracy, consistency and reliability of LiDAR datasets.
• Develop and apply QA/QC protocols for LiDAR data and metadata.
• Collaborate with data engineers, GIS specialists and field teams.
• Run QA tests on LiDAR data (Density, Accuracy, Nomenclature, Landuse, Coverage).
• Prepare technical reports and presentations on QA results.

Skills

Python

MATLAB

R

IDL

JavaScript

Geospatial data validation

Communication skills

Project management

Six Sigma/LEAN

Education

Master in Computer Science or Geoinformation Science

Bachelor with exposure to Data Science

Tools

SPC/Quality tools

Job description

Grow your career with us

You are on a journey to join an exciting Company and be part of our success story to improve lives by developing resources sustainably. Here we offer you an exciting and dynamic work environment and will equip you with the know-how that will stretch and enhance your career journey.

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:

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

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