Cloudera Data Engineer
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Key skills for this role
About the Role
Responsibilities: · Design, develop, and maintain big data solutions using technologies like Hadoop, HBase, Kafka, Hive, Spark, Scala, Python, R, TensorFlow, etc. · Develop and manage data pipelines, migrations, and analytics pipelines in on-premise and cloud environments (Cloudera, AWS, Azure, Google Cloud).
Key Skills for This Role
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Responsibilities
· Design, develop, and maintain big data solutions using technologies like Hadoop, HBase, Kafka, Hive, Spark, Scala, Python, R, TensorFlow, etc.
· Develop and manage data pipelines, migrations, and analytics pipelines in on-premise and cloud environments (Cloudera, AWS, Azure, Google Cloud).
· Utilize open-source kernels and understand distributed compute, distributed storage, serverless, and extremely scalable architectures.
· Collaborate with cross-functional teams to design and implement scalable and efficient data solutions.
· Stay updated with the latest trends and advancements in big data technologies and integrate them into existing systems where applicable.
· Conduct data modeling and analysis to optimize data storage and retrieval processes.
· Provide leadership and mentorship to junior team members.
· Communicate effectively with stakeholders to understand requirements and present solutions.
Requirements
· Bachelor's degree in Computer Science, Information Systems, Business, or related field.
· 8-10 years of experience in data engineering with a focus on big data projects.
· Proficiency in programming languages like Python, Scala, or Java.
· Strong hands-on experience with big data technologies such as Hadoop, HBase, Kafka, Hive, Spark, etc.
· Experience working with open-source kernels and understanding of distributed compute, distributed storage, serverless, and extremely scalable architectures.
· Experience in managing industry-standard programs in on-premise and cloud environments for building data pipelines, migrations, and analytics pipelines.
· Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
· Knowledge and exposure to artificial intelligence, natural language processing, machine learning, statistical analysis, predictive modeling, and time series analysis.
· Familiarity with CI/CD practices.
· Excellent leadership, communication, and presentation skills.
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