Key Responsibilities:

Design and develop data processing applications using Spark to support various business use cases.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Develop and maintain ETL pipelines to extract, transform, and load data from various sources into Spark.
Optimize and tune Spark applications to ensure high performance and scalability.
Troubleshoot and resolve issues related to data processing, data quality, and data integrity.
Monitor and maintain the health and stability of Spark clusters.
Stay updated with the latest Spark technologies and industry best practices to continuously improve our data processing capabilities.

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Minimum of 3 years of experience in developing data processing applications using Spark.
Proficient in programming languages such as Scala, Java, or Python.
Strong understanding of data structures, algorithms, and distributed computing concepts.
Experience with big data technologies such as Hadoop, Hive, and Kafka.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
Ability to work in a fast-paced and dynamic environment.

Join us and be a part of our exciting journey towards leveraging data to drive business growth.

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