Senior Data Engineer
Rad AI- Full Time
- Senior (5 to 8 years)
Candidates should possess 5+ years of data engineering experience, with a significant portion focused on on-premise systems such as Hadoop and HDFS, and demonstrated consistency with tenure at companies (e.g., average of 2+ years). Practical knowledge of engineering best practices, emphasizing system robustness and maintainability, is required, along with expertise in tools like Airflow, Kafka, Spark, and Hive. Advanced proficiency in Python and Java/Scala, with deep knowledge of one language, and advanced working knowledge of SQL and experience with various database dialects are also necessary.
As a Senior Data Engineer, you will design and build scalable data pipelines using tools such as Airflow, Spark, and Kafka, monitor and alert for data quality issues, support data governance and lineage initiatives, contribute to the development of the shared data platform for critical use cases like product analytics, and enhance operational excellence by identifying and implementing improvements in system reliability and performance. You will also work to troubleshoot systems and pipelines for performance and scaling, and communicate effectively with technical and non-technical stakeholders to produce clear technical designs.
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