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Description:
Design, develop, and maintain scalable and efficient big data infrastructure, including data storage, processing, and retrieval systems.
Develop algorithms, scripts, and pipelines for processing, cleaning, and analyzing large volumes of data from various sources.
Implement distributed computing frameworks and technologies (e.g., Hadoop, Apache Sqoop, Kafka, Apache Spark, Airflow) to process and analyze data in parallel across clusters of machines.
Develop data visualization tools and dashboards to present insights and findings in a clear and actionable manner for stakeholders.
Monitor the health and performance of big data systems, troubleshoot issues, and perform routine maintenance tasks to ensure system reliability and availability.
Collaborate with data scientists, analysts, and business stakeholders to understand requirements, gather feedback, and deliver solutions that meet business needs.
Stay informed about emerging technologies and trends in big data and contribute to research efforts to explore new techniques and tools for data processing and analysis.
Prepare comprehensive technical documentation for developed systems and provide ongoing technical support and guidance to team members as needed.
Requirements:
Bachelor's Degree in Computer Engineering/Science, or equivalent practical experience
Minimum 2+ Years of Big Data Engineering experience required
In-depth knowledge of Hadoop, Apache Sqoop, Kafka, Apache Spark, Airflow and similar frameworks
Good knowledge of Big Data querying tools, such as Hive, and Hbase
Minimum 1 year of experience with Java.
Minimum 1 year of experience with Python.
Knowledge of scripting languages including shell scripting and Python