Scripting and Automation:

Develop and maintain scripts for automating data processes and workflows. Troubleshooting:

Diagnose and resolve technical issues related to big data systems, data pipelines, and integrations. Integration Testing:

Conduct thorough testing to ensure seamless integration of new tools and technologies into existing systems. Linux Internals:

Utilize in-depth knowledge of Linux internals to optimize performance and reliability of big data infrastructure. Network Protocols:

Apply understanding of TCP/IP and OSI models in the design and troubleshooting of networked systems. Data Pipeline Support:

Manage and optimize data pipelines and orchestration tools such as NiFi and Airflow. Scalable System Design:

Design scalable big data systems with a focus on security, GDPR compliance, and privacy Hybrid Cloud Management:

Leverage hybrid cloud experience to manage on-premise and AWS cloud resources effectively Data Science Support:

Support data science, machine learning, and AI workloads using tools like Jupyter, Spacy, Transformers, and NLTK. Big Data Platforms:

Utilize big data NoSQL engines and platforms such as Hive, Impala, and Elasticsearch for data storage and processing BI and Visualization:

Implement and support business intelligence and visualization tools like Tableau, Kibana, and PowerBI to provide actionable insights. Strong troubleshooting skills and the ability to diagnose and resolve complex technical issues. Experience with integration testing and ensuring seamless tool integration. In-depth knowledge of Linux internals and system administration. Understanding of TCP/IP and OSI models. Hands-on experience with data pipeline tools like NiFi and Airflow. Proven ability to design scalable big data systems with a focus on security and GDPR compliance. Hybrid cloud experience, specifically with on-premise and AWS cloud environments. Familiarity with data science, machine learning, and AI tools such as Jupyter, Spacy, Transformers, and NLTK. Experience with big data NoSQL engines/platforms such as Hive, Impala, and Elasticsearch. Proficiency with business intelligence and visualization tools like Tableau, Kibana, and PowerBI. Excellent communication and collaboration skills. Certification in AWS or other cloud platforms. Experience with additional data orchestration tools. Familiarity with other big data tools and technologies. Previous experience in a similar role within a dynamic and fast-paced environment. Experience in Cloudera, Hadoop, Cloudera Data Science Workbench (CDSW), Cloudera Machine Learning (CML) would be highly desirable.