Java Developer - Data Processing Solutions

Wissen Technology is seeking a skilled Java Developer to join our dynamic Agile team in Bangalore. You will be instrumental in building scalable data processing solutions, contributing to high-performance data pipelines and analytics platforms. This is a permanent position offering an exciting opportunity to work with cutting-edge technologies.

Responsibilities

• Design and develop robust Java applications, integrating with Apache Spark for efficient ETL processes, data transformations, and advanced analytics.
• Build and optimize Spark jobs, including Spark SQL, DataFrames, and Spark Streaming, to handle large-scale data processing requirements.
• Collaborate closely with data engineers and analysts to implement and maintain reliable data workflows.
• Write clean, well-documented, and maintainable Java code, adhering to best practices, with a preference for Spring Boot and microservices architecture.
• Conduct thorough code reviews and unit testing, and actively contribute to the development and maintenance of CI/CD pipelines.
• Troubleshoot and optimize the performance of Spark applications for production environments.
• Document technical designs and solutions, and provide mentorship to junior developers within the team.

Requirements

• 4 to 7 years of professional experience in Java development.
• Strong hands-on experience with Apache Spark (including Spark Core, Spark SQL, and foundational PySpark knowledge).
• Proficiency in Java 8/11+, with a solid understanding of multithreading and Java Collections Framework.
• Demonstrated experience in data processing, including ETL pipelines and big data technologies.
• Familiarity with essential build tools like Maven or Gradle, and version control systems such as Git.
• Excellent problem-solving capabilities and the ability to work effectively from our Bangalore location.
• Strong communication skills to facilitate seamless collaboration across teams.

Good to Have

• Experience with Snowflake for cloud data warehousing.
• Knowledge of DBT (Data Build Tool) for analytics engineering workflows.
• Proficiency in Python scripting for data manipulation and automation tasks.
• Exposure to major cloud platforms like AWS, GCP, or Azure.
• Familiarity with messaging queues (Kafka), workflow orchestrators (Airflow), or containerization technologies (Docker/Kubernetes).