Data Engineer with Hadoop and Java

Fine With Relocation

Role : Hadoop Data Engineer

Location: Scottsdale, AZ (100% Onsite)

Hire Type : Contract

Contract

End client - Service base company

Experience - 10+ Years.

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.