Senior Spark Analytics Engineer

The Role

A Senior Spark Analytics Engineer plays a pivotal role in designing, developing, and optimizing big data pipelines using Apache Spark to enable advanced analytics and data-driven decision-making. This role involves working closely with data scientists, analysts, and engineering teams to ensure efficient data processing, transformation, and storage across distributed systems. The engineer is responsible for implementing scalable ETL solutions, maintaining high data quality, and tuning Spark jobs for performance. A deep understanding of data architecture, proficiency in programming languages like Scala, Python, or Java, and experience with cloud platforms such as AWS, Azure, or GCP are essential. Strong problem-solving skills and the ability to lead and mentor junior engineers round out the profile of a successful Senior Spark Analytics Engineer.

Experience

6+ Years

Skills

Design and develop analytics workloads using Apache Spark and Scala for processing of big data Create and optimize data transformation pipelines using Spark or Apache Flink Migrate existing analytics workloads from cloud platforms to open-source Apache Spark infrastructure running on Kubernetes – Implement performance optimization techniques for large-scale data processing

Education

Bachelor’s Degree in Computer Science, Information Technology, or a related field.