Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Distributed Systems @ 7
Leadership @ 4
Communication @ 7
API @ 7
Compliance @ 4
Observability @ 4
AI @ 4
Data Pipelines @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100 trust GitLab to ship better, more secure software faster.
The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.
Responsibilities
- Lead the Analytics engineering organization with accountability for strategy, architecture, execution, and team health; measure success through roadmap delivery, service reliability, and organizational effectiveness.
- Guide Engineering Managers and partner with Principal Engineers to set technical direction and support key architectural decisions.
- Define the roadmap for analytics capabilities across instrumentation, data foundations, and customer-facing data products; measure success through adoption, usage, and customer value.
- Oversee the design and operation of end-to-end data pipelines, including instrumentation, ingestion, transformation, storage, serving, and product integration; accountable for data quality, freshness, latency, and reliability.
- Drive platform and architecture decisions that support GitLab's SaaS, self-managed, and regulated or isolated (including air-gapped) deployment environments.
- Collaborate with Product, UX, Infrastructure, Data, and AI leaders to align roadmap, architecture, and execution.
- Build a high-performing engineering organization with clear ownership, strong operational discipline, and consistent technical standards to improve delivery predictability and operational health.
- Champion asynchronous ways of working and AI-assisted development workflows to increase engineering focus, throughput, and delivery quality.
Requirements
- Experience leading multiple engineering teams through managers in a Director-level or comparable engineering leadership role.
- Strong knowledge of distributed systems and large-scale platform engineering.
- Deep understanding of end-to-end data pipelines, analytics platforms, and the technical tradeoffs involved in building them (instrumentation, telemetry, ingestion, transformation, storage, serving, queryable APIs, dashboards).
- Ability to engage deeply in architecture, system design, and technical discussions with senior and principal engineers.
- Experience delivering platforms across SaaS, self-managed, and regulated or isolated deployment environments (including air-gapped deployments).
- Commitment to engineering practices such as test-driven development, continuous delivery, and modular architecture.
- Strong cross-functional communication and leadership skills in a distributed, remote-first environment.
- Interest in transferable experience from adjacent areas such as product analytics, instrumentation, observability, or privacy-conscious analytics systems.
About the team
The Analytics Stage team owns GitLab's analytics platform and analytics product surface. The organization includes Data Products, Instrumentation, and Data Foundations, and builds systems that turn product, usage, billing, and cost data into trusted instrumentation, scalable data foundations, queryable APIs, dashboards, and customer-facing analytics experiences. The team works asynchronously across regions and partners closely with Product, Data, UX, Infrastructure, and AI to solve challenges in scale, privacy, reliability, and deployment flexibility across SaaS, self-managed, and air-gapped environments.
Compensation
United States base salary range: $203,200 - $345,600 USD (base salary range shown is for residents of the United States; does not include bonuses, equity, or benefits).
Benefits
- Benefits to support health, finances, and well-being
- Flexible Paid Time Off
- Team Member Resource Groups
- Equity Compensation & Employee Stock Purchase Plan
- Growth and Development Fund
- Parental Leave