Staff Data Engineer - AI Platform

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.