This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer - AI Platform based in the Canada.
This is a staff-level engineering opportunity focused on the architecture, reliability, and performance of critical data infrastructure supporting a high-availability government cloud environment. You’ll work on a distributed serving layer that transforms complex datasets into fast, dependable answers for mission-critical investigations. The role combines deep data engineering, distributed systems, database optimization, production operations, and AI-assisted development. You’ll have broad technical ownership and play a key role in strengthening infrastructure resilience, scalability, and compliance. The environment is fast-moving and highly collaborative, with engineers empowered to make technical decisions close to the systems they operate. You’ll partner across data platform, product, and forward-deployed engineering teams while tackling technically challenging problems with real-world impact. This role is ideal for an experienced engineer who thrives on autonomy, ambiguity, high standards, and meaningful technical challenges.
Accountabilities
- Lead data infrastructure strategy: Provide technical leadership for the distributed serving layer and help shape its architecture, scalability, performance, reliability, and long-term evolution.
- Own database performance: Drive performance optimization for the serving layer, using advanced query profiling and AI-assisted tooling to identify bottlenecks and resolve inefficient query patterns before they affect customers.
- Build and harden data pipelines: Design, develop, and improve reliable pipelines supporting government cloud investigations, with strong attention to scalability, correctness, maintainability, and compliance.
- Strengthen infrastructure resilience: Reduce single points of failure by becoming a senior independent owner of critical infrastructure and improving system redundancy, operational readiness, and incident response.
- Lead production troubleshooting: Apply sophisticated debugging, log analysis, AI-assisted research, and code exploration to diagnose complex production problems and deliver rapid, durable fixes.
- Drive operational excellence: Participate in on-call responsibilities, improve runbooks and monitoring, lead incident retrospectives, and translate operational learnings into lasting infrastructure improvements.
- Deliver critical infrastructure initiatives: Take complex projects from technical discovery and architectural design through implementation, deployment, validation, and ongoing ownership.
- Support regulatory and compliance needs: Build infrastructure capabilities that satisfy evolving government cloud requirements around availability, auditing, data retention, backups, security, and operational controls.
- Champion AI-enabled engineering: Use AI tools to accelerate development, debugging, code reviews, documentation, configuration, research, and other workflows while maintaining rigorous technical standards.
- Influence technical direction: Make evidence-based architectural and engineering decisions, communicate trade-offs clearly, and contribute technical perspective to broader Data Platform initiatives.
- Mentor and raise engineering standards: Share expertise, improve engineering practices, and help create a culture of strong ownership, craftsmanship, collaboration, and continuous improvement.
- Collaborate across functions: Work closely with Data Platform, Product, Forward Deployed Engineering, and other teams to ensure reliable capabilities and alignment across critical environments.
Requirements
- U.S. citizenship is required due to government cloud data access requirements.
- Extensive hands-on experience designing, operating, and scaling distributed OLAP, analytical database, or serving-layer systems, including technologies such as StarRocks, Trino, ClickHouse, or comparable platforms.
- Deep expertise in query optimization, database performance, distributed systems, and large-scale data infrastructure.
- Strong track record owning data pipeline reliability, production infrastructure, incident response, and operational excellence.
- Demonstrated ability to take end-to-end ownership of complex infrastructure, from architecture and implementation through production operations.
- Experience independently troubleshooting unfamiliar systems and making sound technical decisions in high-pressure production environments.
- Strong experience with on-call operations, incident management, observability, and reliability engineering practices.
- Advanced practical fluency with AI engineering tools such as Claude, Cursor, or similar platforms, using them to accelerate research, debugging, code review, development, documentation, and problem-solving.
- Ability to use AI strategically to improve engineering quality, speed, leverage, and decision-making rather than simply automate repetitive tasks.
- Strong architectural judgment and the ability to evaluate technical trade-offs across performance, reliability, security, compliance, and maintainability.
- Excellent communication and collaboration skills, with the ability to influence technical direction across teams and explain complex concepts clearly.
- Demonstrated leadership through technical influence, mentorship, and the ability to raise engineering standards without relying solely on formal authority.
- Comfortable operating in a high-velocity, high-ownership environment where priorities evolve and ambiguity is part of the work.
- Strong bias toward action, experimentation, continuous learning, and measurable outcomes.
Benefits
- Fully remote work for eligible Canada-based employees.
- Opportunity to provide technical leadership over sophisticated data infrastructure supporting mission-critical government cloud applications.
- Significant autonomy and influence over architecture, infrastructure strategy, technical standards, and operational practices.
- Hands-on exposure to distributed data systems, AI-assisted engineering, production infrastructure, and highly regulated cloud environments.
- Opportunity to solve complex technical problems at the intersection of AI, security, public safety, and mission-critical technology.
- Collaborative distributed-first culture with strong asynchronous communication and close cross-functional partnership.
- Environment that values technical craftsmanship, ownership, experimentation, speed, and continuous improvement.
- Opportunities to mentor other engineers and shape engineering practices across the broader organization.
- Meaningful work with tangible real-world impact and opportunities for continued technical growth.
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!
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.
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