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Anix Global

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Java Application Developer

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Summary

Designs, manages, and optimizes Elasticsearch clusters, indices, and search queries while building large-scale data processing pipelines with Apache Spark and maintaining Java/Spring back-end applications. Core stack: Elasticsearch, Java, Spring, Apache Spark, Python, and Scala.

We are seeking a highly skilled Elasticsearch Engineer with a strong technical background in

Elasticsearch, Apache Spark, Java, Spring, Python, Scala, and various Big Data tools. The ideal

candidate should be a certified Elasticsearch professional with proven expertise in optimizing

search queries and Elasticsearch indices.

Qualification and Skills

  • Minimum of 4 years experience in designing, implementing, and managing Elasticsearch clusters and indices
  • Preferred: Certified Elasticsearch professional with a strong technical background
  • Strong proficiency in Java and the Spring framework for back-end development
  • Hands-on experience with Apache Spark, Python, and Scala for Big Data processing
  • Experience in optimizing search queries and Elasticsearch indices
  • Solid understanding of distributed systems and scalable architecture
  • Excellent problem-solving skills and the ability to work in an Agile development environment
  • Strong communication skills and the ability to collaborate effectively with team members

Responsibilities:

  • Design, implement, and maintain Elasticsearch indices and clusters to ensure efficient data retrieval and storage.
  • Develop and optimize data processing pipelines using Apache Spark for large-scale data analysis and transformation.
  • Collaborate with cross-functional teams to integrate Elasticsearch solutions into existing applications and systems.
  • Implement and maintain scalable and fault-tolerant Java and Spring-based applications.
  • Work on data modeling, indexing strategies, and query optimization for diverse datasets.
  • Develop and maintain connectors between various systems and Elasticsearch.

Added Advantage

  • Experience with machine learning frameworks and algorithms
  • Knowledge of containerization and orchestration tools, such as Docker and Kubernetes
  • Previous exposure to real-time data processing and analytics

Skills

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