Data Infrastructure Specialist

2 days ago

Bengaluru, Karnataka, India beBeeGeospatial Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Geospatial Data Engineer Role Overview

We are seeking a skilled Geospatial Data Engineer to design, build, and maintain data infrastructure and systems that handle geospatial information effectively. Your primary responsibility will be to work closely with cross-functional teams, including data scientists, geospatial analysts, and software engineers, to ensure that geospatial data is collected, processed, stored, and analyzed efficiently and accurately.

Key Responsibilities:
  • Data Pipeline Development: Design and implement robust data pipelines to acquire, ingest, clean, transform, and process geospatial data from various sources such as satellites, aerial, drones, and geolocation services.
  • Data Ingestion, Storage and Extraction: Develop data models and schemas tailored to geospatial data structures, ensuring optimal performance and scalability for storage and retrieval operations.
  • Spatial Database Management: Manage geospatial databases, including both traditional relational databases (e.g., PostgreSQL with PostGIS extension) and NoSQL databases (e.g., MongoDB, Cassandra) to store and query spatial data efficiently.
  • Geospatial Analysis Tools Integration: Integrate geospatial analysis tools and libraries (e.g., GDAL, GeoPandas, Fiona) into data processing pipelines and analytics workflows to perform spatial data analysis, visualization, and geoprocessing tasks.
  • Geospatial Data Visualization: Collaborate with data visualization specialists to create interactive maps, dashboards, and visualizations that effectively communicate geospatial insights and patterns to stakeholders.
  • Performance Optimization: Identify and address performance bottlenecks in data processing and storage systems, leveraging techniques such as indexing, partitioning, and parallelization to optimize geospatial data workflows.
  • Data Quality Assurance: Implement data quality checks and validation procedures to ensure the accuracy, completeness, and consistency of geospatial data throughout the data lifecycle.
  • Geospatial Data Governance: Establish data governance policies and standards specific to geospatial data, including metadata management, data privacy, and compliance with geospatial regulations and standards (e.g., INSPIRE, OGC).

Requirements:

  • Must-have:
    • Bachelor's or Master's degree in Computer Science or a related field.
    • 3-5 years of experience working in the field and deploying the pipelines in production.
    • Strong programming skills in languages such as Python, Java, or Scala, with experience in geospatial libraries and frameworks (e.g., Rasterio, Shapely).
    • Experience with distributed computing frameworks (e.g., Apache Spark, Airflow) and cloud-based data platforms (e.g., AWS, Azure, Google Cloud Platform).
    • Familiarity with geospatial data formats and standards (e.g., GeoJSON, Shapefile, KML) and geospatial data visualization tools (e.g., Mapbox, Leaflet, Tableau).
    • Strong analytical and problem-solving skills, with the ability to work with large and complex geospatial datasets.
  • Good-to-have:
    • Proficiency in SQL and experience with geospatial extensions for relational databases (e.g., PostGIS).
    • Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
    • Nice to have experience with geospatial libraries such as Rasterio, Xarray, Geopandas, and GDAL.
    • Nice to have Knowledge of distributed computing frameworks such as Dask.
    • STAC, GeoParquet, Cloud native tools.
    • Productionising Data Science code.

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