Overview
Skills
Job Details
Job Title: Data Engineer with PySpark, Spark, Python, Hadoop experience Experience: 12 years
Job Summary: With a focus on Apache Hadoop, Python, and Spark, the candidate will develop and implement data-driven strategies. This hybrid role offers the opportunity to work with cutting-edge technologies in a dynamic environment, contributing to impactful projects that enhance the company's geospatial capabilities.
Required Skills: Apache Hadoop, Hadoop, Python, Spark Pyspark, PySpark
Responsibilities: - Develop and implement geospatial data solutions using Apache Hadoop and Spark to drive business insights. - Collaborate with cross-functional teams to integrate geospatial data into existing systems and workflows. - Analyze complex datasets using Python and PySpark to identify trends and patterns that inform decision-making. - Design and optimize data pipelines for efficient processing and storage of geospatial information. - Provide technical expertise in the deployment and maintenance of geospatial data platforms. - Ensure data quality and integrity through rigorous testing and validation processes. - Lead the development of innovative geospatial applications that enhance user experience and functionality. - Oversee the integration of geospatial data with other data sources to create comprehensive datasets. - Mentor junior engineers in best practices for geospatial data analysis and application development. - Stay updated with the latest advancements in geospatial technologies and incorporate them into projects. - Collaborate with stakeholders to understand business needs and translate them into technical requirements. - Document processes and methodologies to ensure knowledge transfer and continuity. - Contribute to the company's strategic goals by delivering high-quality geospatial solutions that impact society positively.
Qualifications: - Possess a strong background in Apache Hadoop and Spark for geospatial data processing. - Demonstrate proficiency in Python and PySpark for data analysis and application development. - Have experience in designing and optimizing data pipelines for large-scale data environments. - Show expertise in integrating geospatial data with other data sources for comprehensive analysis. - Exhibit strong problem-solving skills and the ability to work collaboratively in a hybrid work model.