Senior Software Developer - Data Delivery (Data Engineering)

Location: Toronto, Ontario, Canada

Salary: CAD 107,000–157,300 per year starting base salary, with potential additional bonuses, stock grants, and benefits.

Company

hirify.global develops software that helps innovators design and create buildings, vehicles, factories, media, and other products.

What you will do

• Design, build, test, and operate scalable cloud data pipelines, data services, and data delivery workflows.
• Create analytics-ready and AI-ready datasets with structured data models, metadata, documentation, business definitions, and governed access patterns.
• Contribute to technical designs for data-intensive systems with a focus on performance, resiliency, security, maintainability, and cost efficiency.
• Implement production-quality code and infrastructure changes using automated testing, code review, CI/CD, monitoring, logging, alerting, and tracing.
• Collaborate with product owners, engineers, architects, data consumers, and technical leaders to resolve requirements and system tradeoffs.
• Mentor less-experienced engineers through pairing, design feedback, and code reviews while improving documentation, runbooks, and operational practices.

Requirements

• 5+ years of professional data engineering experience.
• Hands-on experience designing, developing, and operating production data pipelines, distributed services, or cloud data platforms.
• Strong knowledge of data modeling, data architecture, storage technologies, transformation workflows, SQL, and query optimization.
• Experience with batch or streaming processing, event-driven systems, message queues, and resilient integration patterns.
• Strong programming skills in one or more of Python, Java, Kotlin, Scala, TypeScript, or Go.
• Ability to work independently, communicate technical tradeoffs, and maintain a strong focus on data quality and production readiness.

Nice to have

• Experience with AWS infrastructure and data engineering services.
• Experience with orchestration, workflow engines, lakehouse or warehouse patterns, and large-scale object storage.
• Experience preparing data for analytics, AI/ML, LLM, or internal intelligence use cases.
• Knowledge of API architecture, SaaS data-handling risks, incident response, and post-incident improvements.

Culture & Benefits

• Work with a global team and remote colleagues across design, product, engineering, and support.
• Collaborative, self-motivated, empathetic, and accountable working environment.
• Compensation may include annual cash bonuses, stock grants, and a comprehensive benefits package.
• In-person onboarding and/or identity verification may be required.