Senior Software Engineer, Data Systems

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Hive.co

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

📣 Marketing

💼 Consulting

📦 Logistics

Marketing • Consulting • Logistics

Hive. co is a comprehensive event marketing platform designed to help event promoters streamline their marketing strategies and enhance ticket sales. It integrates seamlessly with ticketing platforms to provide real-time event and ticket buyer data, allowing for targeted email and SMS campaigns. With features like CRM, automation, and detailed reporting, Hive. co enables event organizers to engage fans effectively, boost attendance, and optimize marketing efforts for festivals, music events, fairs, rodeos, and comedy shows. The platform simplifies data management and audience segmentation, making it a go-to solution for event promoters.

📋 Description

• Design and own a cloud-native big data platform handling audience data for millions of attendees and billions of interactions annually • Design and own ML infrastructure, including feature stores, training pipelines, model serving, and monitoring • Build reliable, low-latency feature and model infrastructure • Own the full data pipeline from change data capture through validation, transformation, and denormalization • Connect data-system performance to customer impact and business outcomes • Treat data as a product by defining SLAs, improving data health, and enabling discoverability • Use AI coding agents such as Claude Code • Build LLM-powered pipelines and autonomous agents to enrich, classify, and act on audience data at scale • Troubleshoot complex ML systems and build durable solutions • Collaborate with product and engineering teams in an ambiguous, fast-changing environment • Help shape Hive’s data/ML infrastructure and team

🎯 Requirements

• 8+ years of hands-on data engineering experience • Proven experience designing, building, and operating large-scale distributed data and ML systems in production • Experience with high-throughput event streams, production SLAs, and failure consequences • Knowledge of supervised and unsupervised learning, cross-validation, bias–variance, regularization, and evaluation metrics • Knowledge of regression, tree ensembles, and clustering algorithms • Python ML tooling experience, including pandas and scikit-learn • Familiarity with PyTorch or TensorFlow • Experience building production ML pipelines and feature datasets for model training and inference • MLOps experience with experiment tracking, model versioning/registry, deployment, and drift/data-quality monitoring • Strong distributed-systems foundations, including partitioning, consistency models, backpressure, fault tolerance, and capacity planning • Production experience applying LLMs and agentic systems in data or ML contexts • Product and commercial orientation with ability to connect technical decisions to customer impact and business outcomes • Stakeholder communication skills for non-technical audiences • Ability to operate independently in ambiguous, fast-changing environments • Strong troubleshooting skills for complex ML systems • Nice to have: end-to-end data-platform ownership or re-architecture experience • Nice to have: SaaS or event-driven product experience • Eligible to work in Canada without current or future employer sponsorship

🏖️ Benefits

• Meaningful salary and equity • Work fully remote from the comfort of your home • Flexible work hours: minimal meetings and no 9-5 • Health & Dental coverage • Parental Leave top-ups in addition to EI benefits • Unlimited vacation/PTO • Work-life balance