Senior Data Engineer - Geospatial and Big Data We are seeking an experienced Senior Data Engineer to help develop and scale a data platform focused on geospatial and sensor analytics. The role involves building end-to-end systems that process, integrate, and analyse large datasets to deliver real-time insights for operational and analytical use. You will work with engineers, analysts, and product teams to enhance data architecture, performance, and analytical capabilities across the platform. Key Responsibilities Design and maintain data pipelines to process large geospatial and sensor datasets. Develop distributed systems using tools such as Apache Spark, Kafka, and Hadoop. Integrate diverse data sources including satellite, remote sensing, IoT, and GIS feeds. Build analytical models and workflows to detect patterns, predict outcomes, and enable spatial analysis. Implement streaming and real-time data systems to support decision-making. Deploy scalable cloud-based data environments using AWS, Azure, or GCP. Use Docker and Kubernetes to manage containerized deployments. Ensure strong data security, governance, and compliance across the platform. Collaborate with technical and business teams to define needs and continuously improve platform performance. Required Experience 5 or more years of experience in data engineering, software development, or platform design. Strong programming ability in Python, Java, or Scala. Knowledge of frameworks such as Spark, Kafka, or Flink. Experience working with geospatial data and tools including PostGIS, GDAL, or GeoServer. Strong SQL and NoSQL experience, including data warehousing and ETL development. Experience with cloud environments such as AWS, Azure, or GCP. Good understanding of containerization with Docker and orchestration using Kubernetes. Familiarity with data privacy, encryption, and access management standards. Understanding of machine learning principles for pattern detection or predictive analytics. Preferred Qualifications Degree in Computer Science, Data Science, Engineering, or similar. Knowledge of visualization tools such as Tableau, Mapbox, or D3. Experience with real-time streaming frameworks like Kafka Streams or Apache Flink. Background in geospatial or environmental intelligence projects. Understanding of coordinate systems, spatial projections, and data formatting standards.