Senior Data Engineer
Rad AI- Full Time
- Senior (5 to 8 years)
Candidates should possess 5+ years of data engineering experience, with a significant focus on on-premise systems such as Hadoop and HDFS, and demonstrate consistency with tenure at companies, ideally averaging 2+ years per engagement. Practical knowledge of engineering best practices, particularly regarding 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 with experience across various database dialects are also necessary. Exposure to architectural/system design or technical leadership tasks and experience in data governance, data lineage, and data quality initiatives are desirable.
As a Senior Data Engineer, you will design and build scalable data pipelines using tools like Airflow, Spark, and Kafka, monitor and alert for data quality issues, and support data governance and lineage initiatives. You will contribute to the design and improvement of the shared data platform, enabling critical use cases such as product analytics, bot detection, and image classification. Furthermore, you will enhance operational excellence by identifying and implementing improvements in system reliability, maintainability, and performance, and effectively communicate technical designs to both technical and non-technical stakeholders.
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