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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
Analytics Engineers sit at the intersection of business teams, Data Analytics and Data Engineering and are responsible for bringing robust, efficient, and integrated data models and products to life. Analytics Engineers speak the language of business teams and technical teams, they are able to translate data insights and analysis needs into models powered by the Enterprise Data Platform. The successful Analytics Engineer is able to blend business acumen with technical expertise and transition between business strategy and data development.
What You’ll Do
- Serve as the Directly Responsible Individual for major sections of the Enterprise Dimensional Model
- Design, develop, and extend dbt code to extend the Enterprise Dimensional Model
- Approve data model changes as a Data Team Reviewer and code owner for specific database and data model schemas
- Provide data modeling expertise to all GitLab teams through code reviews, pairing, and training to help deliver optimal, DRY, and scalable database designs and queries in Snowflake and Tableau.
- Own one or more stakeholder relationship in Go To Market, Research & Development, or General & Administrative business functions
- Serve as Data Model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately
- Advocate for the Data Quality Program and Trusted Data to help ensure all data is profiled, reviewed, and accurate to support critical decisions
- Guide Work Breakdown Sessions
- Organize and Plan quarter-long development initiatives per the Data Team Planning Drumbeat
What You’ll Bring
- 6+ years in the Data space as an analyst, engineer, scientist, or equivalent
- 2+ years managing the same data model system over time, evolving the model to meet new business requirements
- Demonstrated experience leading 4 or more analytics projects from beginning to operationalization
- Demonstrated experience designing and socializing Entity Relationship Diagrams and reference SQL scripts to scale data acumen and adoption
- Experience working with multiple commercial data warehouses, ETL tools, and data visualization tools
- Extensive experience in 2 or more major data subject areas (marketing, sales, finance, product, people, etc.)
- Ability to use GitLab
- Ability to thrive in a fully remote organization
- Positive and solution-oriented mindset
- Comfort working in a highly agile, intensely iterative environment
- Self-motivated and self-managing, with task organizational skills
- Great communication: Regularly achieve consensus amongst technical and business teams
- Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations
- Demonstrated experience with one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people
- 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.
The base salary range for this role’s listed level is currently for residents of listed locations only. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, and alignment with market data. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
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.
Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us.
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.
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