Key Responsibilities:

Design, build and maintain scalable and reliable Spark data pipelines to process large volumes of data
Optimize and tune Spark jobs for performance and scalability
Develop and maintain data infrastructure on cloud platforms such as AWS, Azure or GCP
Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs
Troubleshoot and resolve any issues related to data quality or system performance
Stay up-to-date with emerging technologies and industry best practices in big data and data engineering
Contribute to the development of data governance and security policies
Document technical specifications and provide support for data-related queries

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Minimum of 3 years of experience in data engineering, with a focus on Spark
Strong understanding of distributed systems and parallel computing
Experience working with cloud-based data platforms and services (AWS, Azure, GCP)
Proficient in programming languages such as Scala, Java, or Python
Knowledge of SQL and database design principles
Familiarity with data warehousing and ETL processes
Excellent problem-solving and analytical skills
Ability to work independently and in a team environment
Strong communication and collaboration skills

As a Spark Engineer, you will have the opportunity to work with cutting-edge technologies and make a significant impact on our data-driven organization. If you are passionate about big data and have a strong desire to continuously learn and grow, we would love to hear from you. Apply now and join our team of talented Spark Engineers!

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