[Hiring] Senior Software Engineer, Data @hive.co

Role Description

As a Senior Data Engineer at Hive, you’ll play a vital role in evolving our data platform, which directly determines what our customers can do, how fast our product moves, and how confidently leadership can make bets. You'll own outcomes, not tickets. If a business metric is off and it touches data, that's yours to care about.

• Build our Data Platform:
  • Design and own a cloud-native big data platform handling audience data for millions of attendees and billions of interactions a year.
  • Build the infrastructure that determines the quality of every insight, recommendation, and decision Hive's customers make.
• Build our ML Platform:
  • Design and own the infrastructure that takes models from experiment to production — feature stores, training pipelines, model serving, and monitoring.
  • Ensure reliable, low-latency access to the features and infrastructure needed to build and ship models confidently.
  • Implement observability to catch model degradation before it affects customers.
• Own the Full Pipeline — and Its Business Impact:
  • Drive the stack end to end from Change Data Capture through validation, transformation, and denormalization.
  • Understand the impact on customers when pipelines are late, metrics drift, or models receive stale data.
• Treat Data as a Product:
  • Ship data products that internal teams and customers depend on like a production API.
  • Define SLAs, obsess over data health, and build for discoverability.
• Build and Leverage Agentic Systems:
  • Bring an agentic engineering mindset to everything — both how you work and what you build.
  • Use AI coding agents as a force multiplier and build LLM-powered pipelines and autonomous agents that enrich, classify, and act on audience data at scale.

Qualifications

• 8+ years of hands-on data engineering experience, with a proven track record of designing, building, and operating large-scale distributed data systems in production.
• Strong foundations in distributed systems principles — partitioning strategies, consistency models, backpressure handling, fault tolerance, and capacity planning.
• End-to-end ML engineering experience: feature engineering and feature store design, training pipeline orchestration, model deployment and serving infrastructure, and production monitoring.
• Experience applying LLMs and agentic systems in production data or ML contexts.
• A product and commercial orientation — consistently frame technical decisions in terms of customer impact and business outcomes.

Requirements

• Comfortable operating independently and making progress in ambiguous, fast-changing environments.
• Biased toward action; willing to make decisions with imperfect information and iterate quickly.
• Skilled at troubleshooting complex systems and building durable solutions when things break.
• Excited to shape the future of Hive’s data infrastructure and team in a high-growth, fast-paced company.

Benefits

• Meaningful salary and equity: you're rewarded based on impact.
• The compensation range for this role is $123,600 to $187,900 CAD per year, depending on qualifications and experience.
• New team members typically start between $123,600- $155,000 based on experience.
• Work fully remote from the comfort of your home.
• Flexible work hours: minimal meetings and no 9-5.
• Health & Dental coverage with Parental Leave top-ups in addition to EI benefits.
• Unlimited vacation/PTO: so you can be happy and healthy!