Key Responsibilities:

Design, develop, and maintain data processing pipelines using Apache Spark
Collaborate with data scientists and data engineers to understand business requirements and design efficient solutions
Develop and implement data quality checks to ensure accuracy and consistency of data
Optimize data processing pipelines for performance and scalability
Troubleshoot and debug issues in production environments
Coordinate with cross-functional teams to ensure timely delivery of projects
Stay updated with the latest technologies and trends in big data processing and contribute to the improvement of our data infrastructure
Mentor and provide technical guidance to junior team members

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Minimum of 3 years of experience in big data processing using Apache Spark
Strong programming skills in Java, Scala, or Python
Experience with cloud-based big data platforms such as AWS, GCP, or Azure
Knowledge of distributed systems and data processing frameworks such as Hadoop, Hive, or Kafka
Familiarity with SQL and NoSQL databases
Proven track record of delivering scalable and efficient solutions for large datasets
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
Ability to work in a fast-paced and dynamic environment
Experience with Agile methodologies is a plus

Join our team and be a part of our exciting journey towards transforming data into actionable insights.

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