KAFKA, REDIS AND HADOOP DEVELOPER
Job Description
Key Responsibilities
- Design, develop, and maintain real-time data streaming applications using Apache Kafka, including KStreams and KTable.
- Develop scalable big data processing solutions using Hadoop and PySpark.
- Implement and optimize data storage and retrieval using NoSQL databases such as Redis, MongoDB, and HBase.
- Develop data processing and integration pipelines using Python, Scala, Java, and Bash/Shell scripting.
- Build reliable distributed systems with efficient data partitioning, fault tolerance, and high availability.
- Work with streaming technologies such as Apache Flink and Apache Storm.
- Leverage cloud platforms such as AWS, Azure, or GCP for big data processing and deployment.
- Apply data security and integration best practices, including Kerberos authentication.
- Perform data analysis and support predictive modeling using statistical techniques and machine learning algorithms.
- Develop and maintain visual analytics and reporting solutions using Tableau.
- Troubleshoot performance issues, optimize data pipelines, and ensure data quality and reliability.
- Collaborate with cross-functional teams to deliver business-critical data solutions.
- Bachelor's or Master's degree in Science, Engineering, Computer Science, or a related field.
- 9–12 years of overall professional experience in software development and data engineering.
- Strong hands-on experience with Apache Kafka, Redis, Hadoop, and PySpark.
- Proficiency in Python and familiarity with Scala, Java, and Bash/Shell scripting.
- Strong understanding of real-time streaming, distributed computing, and big data architecture.
- Experience with NoSQL databases and cloud-based data processing platforms.
- Knowledge of data security, data integration, and visualization tools such as Tableau.
- Excellent problem-solving, analytical, and communication skills.
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