Spark Developer Job Description

This template is designed to help you create a comprehensive job description for a Spark Developer position. It outlines the key responsibilities, qualifications, and skills necessary for the role, aiming to attract candidates who are proficient in Apache Spark and big data technologies, and align with your organization’s data processing and analytics goals.

A Spark Developer specializes in designing, building, and maintaining big data applications using Apache Spark. They are responsible for developing high-performance data processing solutions that handle large volumes of data efficiently.

Spark Developer Job Description Template

We are looking for a skilled Spark Developer to join our data engineering team. As a Spark Developer, you will be responsible for developing scalable big data applications using Apache Spark. Your role will involve working with large datasets, optimizing Spark jobs for performance, and collaborating with other team members to solve complex data processing challenges.

Spark Developer Responsibilities

• Design, build, and maintain efficient, reusable, and reliable Apache Spark applications.
• Process large amounts of data using Spark RDDs, DataFrames, and Datasets.
• Optimize Spark applications for maximum speed and scalability.
• Implement data ingestion and ETL processes.
• Collaborate with data scientists and architects to implement complex big data solutions.
• Debug and resolve issues in Spark applications.
• Stay up-to-date with the latest trends in big data technologies and Apache Spark.
• Write clean, readable, and maintainable code.
• Participate in code reviews and contribute to team knowledge sharing.

Spark Developer Reports To

• Data Engineering Manager
• Head of Data Science

Spark Developer Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• [X-Y years] of experience in big data technologies, specifically Apache Spark.
• Proficiency in Scala, Java, or Python.
• Strong understanding of Spark’s core API and its libraries like Spark SQL, Streaming, and MLlib.
• Experience with big data ecosystems (Hadoop, Hive, etc.) and databases (SQL/NoSQL).
• Familiarity with data pipeline and workflow management tools.
• Strong problem-solving skills and ability to work in a team environment.
• Excellent communication and analytical skills.