Job descriptionMinimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.High proficiency in Python, Scala and Spark for applied large-scale data processing.Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.Solid understanding of batch and streaming data processing techniques.Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.Expert-level ability to write complex, optimized SQL queries across extensive data volumes.Experience with RDBMS and OLAP databases like MySQL, Snowflake.Familiarity with Agile methodologies.Obsession for service observability, instrumentation, monitoring, and alerting.Knowledge or experience in architectural best practices for building data lakes.