Senior Manager, Analytics Engineering (R&D)

GitLab is an open core software company that develops the most comprehensive AI-powered DevSecOps Platform, used by more than 100,000 organizations. Our mission is to enable everyone to contribute to and co-create the software that powers our world. When everyone can contribute, consumers become contributors, significantly accelerating the rate of human progress. This mission is integral to our culture, influencing how we hire, build products, and lead our industry. We make this possible at GitLab by running our operations on our product and staying aligned with our values. Learn more about Life at GitLab.

Thanks to products like Duo Enterprise, and Duo Workflow, customers get the benefit of AI at every stage of the SDLC. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier. All team members are encouraged and expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact across our global organization.

An overview of this role

The Senior Manager, Analytics Engineering (R&D) sits at the intersection of Business Strategy, Analytics Engineering, and Data Engineering and is responsible for leading a team that brings robust, efficient, and integrated data products to life. The Senior Manager, Analytics Engineering (R&D) speaks the language of business teams and technical teams, able to translate data insights and analysis needs into data models powered by the Enterprise Data Platform. The successful Senior Manager, Analytics Engineering (R&D) is able to blend business acumen with technical expertise and transition between business strategy and data development. In this role, the incumbent will have an opportunity to drive impact on a large scale by leading a team that delivers trusted data that is used by Senior Leadership to power Customer Product Adoption at GitLab.

What You’ll Do  

• Manage, lead, and develop a high-performance Analytics Engineering team specializing in Product Usage data, including day-to-day assignments, bi-weekly milestone planning, 1-1s, quarterly objectives, and annual reviews
• Lead the development of sophisticated data models that transform complex event-level usage data from our product into actionable business insights
• Player/Coach that can both lead a team of expert data modelers and make hands-on contributions to our most challenging Product Usage data transformations and modeling initiatives
• Understand the big picture of product adoption and user behavior, demonstrating how your team's Product Usage data models support strategic decision-making through prioritization, planning, and advanced solutioning
• Architect and oversee the implementation of scalable data pipelines that process high-volume, real-time product usage events into reliable, performant data models
• Collaborate closely with Product, Engineering, and Business Strategy teams to translate complex usage patterns and behavioral analytics requirements into robust data model specifications

What You’ll Bring 

• Share our values, and work in accordance with those values
• 5+ years hands on experience in a data analytics/engineering/science role
• 2+ years hands on experience performing quantitative analysis to tackle business problems with a focus on feature and usage metrics to increase conversion and retention
• 1+ years hands on experience creating dimensional models composed of facts and dimensions
• 1+ years leading or managing a team of 3 or more data analysts/engineers/scientists
• Demonstrate ability to understand and communicate end-to-end data systems: from compute to ELT to Reporting to Analysis
• Exceptional experience creating and developing partnerships with internal team members towards delivery of impactful analytics solutions
• Experience defining and executing project plans at the day, week, and month time spans
• Demonstrably deep understanding of SQL and relational databases (we use Snowflake)
• Experience working with large quantities of raw, disorganized data

How GitLab will support you

• 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
• Parental leave 
• Home office support

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.  

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GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.