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Hadoop Data Engineer

Rivago infotech incScottsdale, AZ🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeOn Site
LocationScottsdale, AZ, United States
SQLScalaSpringSpring BootGitApache SparkApacheHadoopHiveJavaKafkaRESTCI/CDMaven

Job description

Role : Hadoop Data Engineer

Location :  Scottsdale AZ (100% Onsite)

Please note: Once the candidate is selected, Day 1 onboarding will be conducted in person at the designated location. All travel expenses which include only to-and-fro travel tickets will be booked by Persistent. Candidates are encouraged to plan accordingly and can be assured that the onboarding experience will be supported from the outset

Key Responsibilities

  • Design, develop, and maintain scalable data processing applications using Java (8 or above) and Spring Boot.
  • Build and optimize big data pipelines using Spark and Scala for large-scale data processing.
  • Develop and consume RESTful web services for data integration and platform interoperability.
  • Implement and manage batch and streaming data pipelines using Spark Streaming and Kafka.
  • Write optimized Hive queries and SQL, focusing on performance and scalability.
  • Work on distributed data platforms leveraging Hadoop ecosystem components.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Ensure code quality through reviews, version control, and CI/CD best practices.
  • Troubleshoot and resolve performance, scalability, and data reliability issues.

Required Skills & Qualifications

  • 8–12 years of hands-on experience in Java (version 8 or above).
  • Strong expertise in Spring Boot framework.
  • Excellent proficiency in Apache Spark and Scala.
  • Strong experience with Hive, SQL optimization, Hadoop, and Kafka.
  • Solid understanding of RESTful web services.
  • Experience with version control systems such as Git / GitLab.
  • Hands-on experience with build tools like Maven and/or Gradle.
  • Strong understanding of distributed systems and big data architecture.
  • Experience with streaming frameworks such as Spark Streaming and Kafka Streams.
  • Experience working in large-scale enterprise data platforms.
  • Exposure to performance tuning and capacity planning for big data systems.
  • Knowledge of DevOps or CI/CD pipelines is a plus.

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