Senior Big Data Engineer - Contract - Atlanta, GA (Hybrid)

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Lorven Technologies, Inc., is seeking the following. Apply via Dice today! Hi, Our client is looking Senior Big Data Engineer for Long-Term Contract project in Atlanta, GA (Hybrid). below is the detailed requirements. Job Role : Senior Big Data Engineer Location : Atlanta, GA (Hybrid) Duration : Long Term Contract Required Skills : Python, PySpark, Hadoop Responsibilities : • Analyze and interpret complex geospatial data using Hadoop, PySpark, and Python to provide actionable insights. • Collaborate with cross-functional teams to integrate geospatial data into business processes and strategies. • Develop and maintain geospatial data models to support various analytical needs. • Ensure data quality and integrity by implementing robust data validation and cleansing processes. • Design and implement efficient data processing pipelines to handle large volumes of geospatial data. • Provide technical expertise and guidance to junior analysts and team members. • Create detailed reports and visualizations to communicate findings to stakeholders. • Stay updated with the latest geospatial technologies and methodologies to enhance analytical capabilities. • Optimize existing geospatial analysis processes to improve efficiency and accuracy. • Contribute to the development of innovative solutions to address complex geospatial challenges. • Support strategic decision-making by providing insights derived from geospatial data analysis. • Work closely with data engineering teams to ensure seamless data integration and accessibility. • Participate in project planning and execution to ensure timely delivery of analytical outputs. Qualifications: • Demonstrate proficiency in Hadoop, PySpark, and Python for geospatial data analysis. • Possess strong analytical and problem-solving skills to interpret complex datasets. • Exhibit excellent communication skills to effectively convey insights to stakeholders. • Have a solid understanding of geospatial data models and processing techniques. • Show experience in developing data processing pipelines for large datasets. • Maintain a proactive approach to learning and adapting to new technologies.