Lead Data Engineer Role at Hive.co
Posted
Summary
Lead Data Engineer at Hive.co building and scaling a cloud-native data platform that powers marketing for major North American events. Day to day: architect the data platform, take ML infrastructure from experimentation to production, deliver data products, and build agentic/LLM systems. Core stack: Python, Django, various data stores, distributed systems, MLOps.
Drive innovation in data engineering at Hive.co as a Lead Data Engineer, focusing on scalable platforms and machine learning solutions. Enjoy a fully remote work environment.
In this leadership role within Hive's R&D Data team, you’ll be responsible for constructing and optimizing our data platform that enables effective marketing strategies for major North American events. Your experience in large-scale data systems will guide the development of infrastructure that provides high-quality insights. This position is pivotal as it bridges technical excellence and business impact in a fast-paced setting.
Key Responsibilities: • Architect and scale our cloud-native data platform • Implement ML infrastructure from experimentation to production • Manage end-to-end data processing and business metric alignment • Deliver data products with strong operational standards • Develop agentic systems for automated data processing
Requirements: • 8+ years of data engineering expertise required • Solid grasp of ML engineering concepts and practices • Proficiency with Python, Django, and various data stores • Familiar with distributed systems and MLOps • Track record of LLM or agentic systems application
Bring your extensive data engineering experience to transform Hive's capabilities and customer engagement.
In this leadership role within Hive's R&D Data team, you’ll be responsible for constructing and optimizing our data platform that enables effective marketing strategies for major North American events. Your experience in large-scale data systems will guide the development of infrastructure that provides high-quality insights. This position is pivotal as it bridges technical excellence and business impact in a fast-paced setting.
Key Responsibilities: • Architect and scale our cloud-native data platform • Implement ML infrastructure from experimentation to production • Manage end-to-end data processing and business metric alignment • Deliver data products with strong operational standards • Develop agentic systems for automated data processing
Requirements: • 8+ years of data engineering expertise required • Solid grasp of ML engineering concepts and practices • Proficiency with Python, Django, and various data stores • Familiar with distributed systems and MLOps • Track record of LLM or agentic systems application
Bring your extensive data engineering experience to transform Hive's capabilities and customer engagement.