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Your work will shape how models learn, reason, and perform through high-quality, real-world input.\nRequired Skills\nbig data\n\nPython\n\ndatabases\n\ndata engineering\n\nKey Responsibilities:\nDesign, build, and maintain scalable big data pipelines and architectures to support robust data solutions.\n\nCollaborate with cross-functional teams to understand and deliver on data requirements and business objectives.\n\nImplement data integration, transformation, and processing solutions using Python and relevant big data technologies.\n\nDevelop, manage, and optimize distributed databases and storage systems for efficiency and reliability.\n\nMonitor, troubleshoot, and enhance data systems to ensure high availability and performance.\n\nEnforce data quality, security, and governance standards across all solutions.\n\nDocument solutions and communicate complex technical concepts effectively, both in writing and verbally.\n\nRequired Skills and Qualifications:\nProven expertise in big data engineering with hands-on experience building and maintaining large-scale data pipelines.\n\nAdvanced proficiency in Python for data processing, automation, and integration.\n\nDeep understanding of relational and NoSQL databases, including optimization and management techniques.\n\nExperience with distributed data processing frameworks (e.g., Hadoop, Spark, Flink).\n\nStrong foundation in data modeling, ETL processes, and data warehousing principles.\n\nExcellent written and verbal communication skills, with the ability to convey technical ideas clearly to both technical and non-technical stakeholders.\n\nDetail-oriented, proactive, and self-motivated, thriving in remote and autonomous work environments.\n\nPreferred Qualifications:\nPrior experience in fast-paced or startup-like environments supporting global teams.\n\nExpertise with cloud-based big data platforms (e.g., AWS, GCP, Azure).\n\nFamiliarity with machine learning operations and data science workflows is a 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