Role : Hadoop Data Engineer
Location : Scottsdale AZ (100% Onsite)
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
· 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.

Hadoop Data Engineer

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