Geospatial Data Lead

Conceptualizing , Creating and implementation of business solutions / frameworks using large geospatial datasets especially with a strong focus towards deriving and delivering contextual business intelligence. Including:

• Ingesting data from multiple sources either online or through sensors / devices and fusing the data to arrive at the most optimal solution
• Building automated ETL pipelines using modern cloud technologies
• Building solutions / teams for automated data labelling/annotation, training, validation.
• Feature identification, pattern recognition and feature extraction
• Automated Image processing preferably (experience in using multiple formats is an advantage 360 / mobile imagery, LiDAR, Drone, RADAR, SAR, Hyperspectral, OSM)
• Standing up GPU processing and cloud architectures for efficient data manipulation.
• Creating services-based architecture combining multiple components towards an outcome.
• Application and industrialization/scale-up (Devops principles for deployment of large scale deployments in real-world production environments).
• Experience of ‘human in the loop’ flowlines but with an emphasis in removing as much of the human element as possible, whilst ensuring sufficient governance and oversight for the creation of good quality outputs.

Desired Skills and Experience

• 12-15 years of experience with an Engineering or Phd from a reputed Institute
• Geospatial software and platforms such as PostGres, Terrasolid, QGIS, FME.
• Geospatial data libraries such as OGR, GDAL
• ML/Deep learning/ Computer Vision frameworks.
• Cloud based architectures.
• Data and automation technology such as Python, Pandas, Tensorflow
• Good technical understanding (and any hands-on exposure/ experience would be even better) of at least 2 or more technologies from the following areas :
• IOT / Edge processing and Analytics
• MetaVerse led solutions /services: Immersive 3D/AR/VR Visualization (Unity 3D / UnReal gaming engine)
• Mobile , Cloud Native Apps
• AI / ML Driven Automated testing / simulation / test drive / Validation
• Big Data processing (Databricks, Kubernetes, Azure data lake/data factory, etc)