Staff Software Engineer, Core Infrastructure

Job description

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. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer, Core Infrastructure based in Canada. This is a high-impact staff-level engineering role focused on building and operating foundational infrastructure for large-scale content and data platforms. You’ll work on distributed storage, data processing, governance, observability, and low-latency retrieval systems serving hundreds of millions of users. The role combines hands-on development with technical leadership, from architecture and implementation through deployment and production operations. You’ll work primarily with Rust and Python across AWS-based infrastructure and modern data technologies. You’ll partner closely with engineering, ML, search, product, and data teams to solve complex scalability, performance, and cost challenges. This is an opportunity to shape a platform that other engineers rely on while raising engineering standards across the organization.