GitLab - Staff Backend Engineer, Analytics Instrumentation (Golang)
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Requirements
• Extensive production experience with Go, with a proven track record of architecting and shipping large-scale services used by multiple teams. • Demonstrated ability to design and own backend systems that scale, with experience shaping architectural choices that influence multiple engineering teams. • Deep expertise in infrastructure concerns including system reliability, performance optimization at scale, data quality, and observability; proven ability to set standards and mentor others in these areas. • Proven experience designing and owning APIs (REST, gRPC, or similar) that scale to serve multiple internal teams, with the ability to evolve designs based on diverse stakeholder needs. • Experience coordinating initiatives across functional boundaries, influencing product teams, data consumers, and other stakeholders through technical vision and mentorship. • Deep expertise in instrumentation, analytics, data systems, or similar foundational infrastructure; demonstrated impact building systems that become critical to company operations. • Our team is part of the Data Engineering organization and runs a foundational service used by all research and development teams at GitLab. We manage the systems that send, transport, and validate instrumentation data across the company, giving us visibility into customer usage patterns across GitLab SaaS and Self-Managed deployment environments. This data informs usage billing and product planning. We're building a unified, Go-based instrumentation service that replaces multiple language-specific SDKs, making it easier for teams to instrument their features while ensuring data integrity for billing and analysis. As a distributed team working asynchronously across multiple time zones, we work closely with product and engineering teams across the company and provide guidance on instrumenting features effectively. • How GitLab Supports Full-Time Employees • Benefits to support your health, finances, and well-being • Flexible Paid Time Off • Team Member Resource Groups • Equity Compensation & Employee Stock Purchase Plan • Growth and Development Fund • Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. • Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. • Country Hiring Guidelines:
Responsibilities
• Architect and guide the design of a unified Go-based instrumentation service, setting the technical direction to replace multiple language-specific SDKs and maintain reliable, high-performance instrumentation across the company. • Own the strategy for handling, validating, and improving instrumentation data quality across the system, increasing billing accuracy and strengthening product planning. • Coordinate mentorship and training initiatives with product development teams across the company, improving adoption of instrumentation best practices and raising the quality and consistency of feature instrumentation. • Set reliability and turnaround standards for systems that enable usage billing and instrumentation, contribute to critical-incident on-call coverage, and coordinate post-incident improvements that reduce recurring issues. • Coordinate cross-functional initiatives across research and development teams and the enterprise data organization, aligning evolving requirements and delivering solutions that serve multiple stakeholders across the company. • Own key architectural choices that balance ease of use for product teams with reliability and correctness for data consumers, establishing patterns that scale the system as a foundational service for company-wide growth.
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