Software Engineer - Scala/Spark
Published date: 2024/01/10
- Location: Jaipur, Rajasthan, India
Designation - Software Engineer
Location - Jaipur, Gurugram
Experience - 3-8 years
Skills - Java, Spark, Kafka, Scala
• Mandatory Java coding experience with Spark, Kafka, Scala
Responsibilities
• Designing, developing, and maintaining robust and scalable data processing applications using Apache Spark and related technologies.
• Writing high-quality, efficient, and maintainable code in Scala and Java to implement data pipelines, transformations, and analytics solutions.
• Collaborating with cross-functional teams, including data scientists, data engineers, and business stakeholders, to understand requirements and deliver innovative solutions.
• Optimizing Spark jobs and clusters for performance and scalability, leveraging various optimization techniques and tuning parameters.
• Integrating Spark applications with Kafka for real-time data ingestion and stream processing.
• Troubleshooting and resolving issues related to Spark, Kafka, and other data processing technologies in production environments.
• Writing comprehensive unit tests and conducting code reviews to ensure code quality and adherence to best practices.
• Documenting design decisions, implementation details, and system architectures for future reference.
(ref:hirist.com
Location - Jaipur, Gurugram
Experience - 3-8 years
Skills - Java, Spark, Kafka, Scala
• Mandatory Java coding experience with Spark, Kafka, Scala
Responsibilities
• Designing, developing, and maintaining robust and scalable data processing applications using Apache Spark and related technologies.
• Writing high-quality, efficient, and maintainable code in Scala and Java to implement data pipelines, transformations, and analytics solutions.
• Collaborating with cross-functional teams, including data scientists, data engineers, and business stakeholders, to understand requirements and deliver innovative solutions.
• Optimizing Spark jobs and clusters for performance and scalability, leveraging various optimization techniques and tuning parameters.
• Integrating Spark applications with Kafka for real-time data ingestion and stream processing.
• Troubleshooting and resolving issues related to Spark, Kafka, and other data processing technologies in production environments.
• Writing comprehensive unit tests and conducting code reviews to ensure code quality and adherence to best practices.
• Documenting design decisions, implementation details, and system architectures for future reference.
(ref:hirist.com
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