Staff Software Engineer, Core Infrastructure

Accountabilities:

• • Design, build, deploy, and operate core Rust services supporting transactional storage, data transformation, and low-latency content retrieval at very large scale.
  • Own software end-to-end, including technical design, implementation, testing, deployment, observability, on-call responsibilities, and production incident response.
  • Evolve Python-based transformation frameworks, tooling, APIs, and developer experiences used by engineering teams across the organization.
  • Lead cross-functional technical initiatives, establishing roadmaps, milestones, architectural decisions, and delivery plans that balance scalability, performance, cost, and speed.
  • Improve system performance and cloud efficiency through query execution optimization, Parquet and Arrow data structures, S3 access patterns, caching, and PostgreSQL/Aurora tuning.
  • Strengthen data governance capabilities, including lineage, authorization, access controls, and reliable deletion propagation across multiple products and environments.
  • Support other engineers through thoughtful code reviews, technical guidance, well-designed APIs, and clear documentation.
  • Produce design documents, runbooks, and technical documentation that create alignment and make systems easier to operate and evolve.
  • Mentor engineers and contribute to improving engineering practices, developer tooling, and the effective use of agentic AI while maintaining strong standards for quality, security, and human ownership.

  Requirements:

  • 10+ years of professional software engineering experience, particularly building backend, distributed, infrastructure, or data-intensive systems.
  • Strong production experience with Rust and solid proficiency in Python.
  • Deep understanding of storage and data technologies, including Amazon S3, Apache Parquet/Arrow, and relational databases such as PostgreSQL or MySQL.
  • Demonstrated experience designing and operating high-throughput, low-latency services, including metrics, tracing, alerting, debugging, and production operations.
  • Strong experience with AWS, including technologies such as S3, Lambda, ECS, and Aurora, as well as infrastructure-as-code practices using tools such as Terraform.
  • Proven technical leadership experience, including leading projects across teams, creating architecture and design documentation, driving alignment, and mentoring engineers.
  • Ability to translate ambiguous requirements into well-defined technical solutions and shipped software.
  • Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.
  • Experience with query engines, database internals, or technologies such as Apache DataFusion, Arrow, arrow-rs, or the Parquet crate is highly desirable.
  • Contributions to open-source projects, particularly within the Rust data ecosystem, are a plus.
  • Experience with data governance at scale, including lineage, access control, privacy requirements, and deletion compliance, is advantageous.
  • A strong FinOps mindset and experience reducing cloud costs through architectural improvements are valuable.
  • Experience creating platforms, SDKs, contribution models, or developer experiences that enable other engineering teams to build efficiently is a plus.
  • Familiarity with agentic engineering tools and workflows, including using AI coding assistants as part of daily development while maintaining human oversight of quality and security, is desirable.

  Benefits:

  • Competitive salary range in Canada of approximately CAD $184,500–$244,500, depending on location, experience, skills, education, and other factors.
  • Competitive equity ownership opportunity.
  • Flexible work model designed to support different working styles and locations, with intentional in-person collaboration when required.
  • Comprehensive health, dental, and vision coverage.
  • Mental health support and disability coverage.
  • Generous paid time off, including vacation, sick leave, holidays, winter break, volunteer time, and sabbatical opportunities.
  • Paid parental leave and family support benefits.
  • Retirement matching.
  • Learning, development, and professional growth opportunities.
  • Wellness and home-office stipends.
  • Complimentary access to the company’s suite of products.
  • Enterprise access to leading AI tools.
  • Eligible Canadian locations include Ottawa, Toronto, and Vancouver, including surrounding metro areas or typical commuting distances.