Senior Data Engineer at Hive
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Summary
Senior Data Engineer at Hive designs and maintains cloud-native big-data and ML infrastructure for large-scale audience data, building end-to-end pipelines with SLAs and implementing LLM-powered data processing. Requires 8+ years in data engineering, strong Python and ML fundamentals, MLOps experience, and distributed systems knowledge.
Elevate your career with Hive as a Senior Data Engineer focused on advancing our data platforms. This fully remote role requires expertise in cloud-native systems and machine learning infrastructure.
Hive's R&D Data team is seeking an experienced engineer who builds and maintains high-performance data solutions. The ideal candidate will design cloud-native architectures for handling massive audience data while ensuring reliable machine learning access. Your role will significantly influence product speed, data reliability, and leadership decision-making through properly managed data.
Key Responsibilities: • Design a cloud-native big data platform for audience insights • Build ML infrastructure for smooth model deployment and monitoring • Manage end-to-end data pipelines with business impact awareness • Deliver data products with defined SLAs for internal and customer use • Implement AI coding agents and LLM-powered systems for data processing
Requirements: • 8+ years in data engineering, focusing on large-scale systems • Strong fundamentals in machine learning concepts and algorithms • Proficiency in Python and relevant ML tooling • Experience in applying MLOps practices • Knowledge of distributed systems principles and real-time data handling
Contribute to Hive’s mission by shaping our data and ML infrastructure with your expertise.
Hive's R&D Data team is seeking an experienced engineer who builds and maintains high-performance data solutions. The ideal candidate will design cloud-native architectures for handling massive audience data while ensuring reliable machine learning access. Your role will significantly influence product speed, data reliability, and leadership decision-making through properly managed data.
Key Responsibilities: • Design a cloud-native big data platform for audience insights • Build ML infrastructure for smooth model deployment and monitoring • Manage end-to-end data pipelines with business impact awareness • Deliver data products with defined SLAs for internal and customer use • Implement AI coding agents and LLM-powered systems for data processing
Requirements: • 8+ years in data engineering, focusing on large-scale systems • Strong fundamentals in machine learning concepts and algorithms • Proficiency in Python and relevant ML tooling • Experience in applying MLOps practices • Knowledge of distributed systems principles and real-time data handling
Contribute to Hive’s mission by shaping our data and ML infrastructure with your expertise.
