Job Description
We are seeking a Senior Data Architect to design and optimize our geospatial data infrastructure, ensuring scalability, performance, and seamless integration with telco systems.
Role Overview: As a Senior Data Architect, you will be responsible for defining the technical vision and architecture for geospatial data pipelines and storage. You will work closely with data engineers, product owners, and telco system teams to ensure data is structured, accessible, and reliable for advanced analytics and operational applications.
Key Responsibilities:
Design and implement scalable data architectures for geospatial datasets, including ingestion, storage, processing, and retrieval.
Develop data models, pipelines, and frameworks to integrate geospatial and telco data efficiently.
Ensure data quality, governance, and security across all geospatial data assets.
Collaborate with cross-functional teams to translate business requirements into technical solutions.
Evaluate and recommend emerging technologies and tools for geospatial data management and analytics.
Provide technical leadership and guidance to data engineering teams.
Optimize existing data architectures for performance, scalability, and cost efficiency.
Requirements
Required Qualifications:
Bachelors or Masters degree in Computer Science, Information Systems, GIS, or related field.
7+ years of experience in data architecture, with a focus on geospatial or telecommunications data.
Strong expertise in cloud-based data storage and processing solutions (AWS, Azure, GCP).
Hands-on experience with geospatial databases and tools (PostGIS, GeoServer, QGIS, or similar).
Proficiency in ETL/ELT processes and data pipeline frameworks (Apache Spark, Kafka, Airflow).
Solid understanding of telco systems, network data, and related protocols.
Knowledge of data modeling, governance, and security best practices.
Excellent problem-solving, communication, and stakeholder management skills.
Preferred Skills:
Experience with real-time geospatial data processing.
Familiarity with AI/ML integration for geospatial analytics.
Certifications in cloud platforms, data architecture, or GIS systems.
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