Key Responsibilities:

Design, develop, and implement scalable and efficient data processing pipelines using Apache Spark.
Work closely with data scientists, data engineers, and business stakeholders to understand requirements and deliver high-quality solutions.
Optimize Spark jobs for performance, scalability, and reliability.
Troubleshoot and debug issues in production environments.
Develop and maintain technical documentation for all projects.
Stay updated with the latest technologies and industry trends in big data and distributed computing.

Qualifications:

Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
Minimum of 3 years of experience working with Apache Spark.
Strong knowledge of programming languages such as Scala, Java, or Python.
Experience with big data technologies including Hadoop, Hive, and Kafka.
Familiarity with SQL and NoSQL databases.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Excellent problem-solving and analytical skills.
Ability to work in a fast-paced, agile environment.
Strong communication and collaboration skills.

Preferred Qualifications:

Experience with Spark streaming and real-time data processing.
Knowledge of machine learning and data science concepts.
Experience with DevOps tools and processes.
Certifications in Apache Spark or related technologies.

Working Conditions:

This is a full-time, on-site position.
Must be able to work in a fast-paced, deadline-driven environment.
Occasional weekend or after-hours work may be required.
Some travel may be required.

If you are a self-motivated individual with a passion for big data and distributed computing, we would love to hear from you. Apply now and join our team of talented and driven professionals.

Hashtags