This position is 100% remote, US Timezone
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, 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.
In this role, you'll have an opportunity to drive impact on a large scale by delivering trusted, transformed data that Senior Leadership will use to power the Customer Journey, Go To Market Motion and Product Intelligence Analytics decisions at GitLab.
Want to learn more about the Data Team and key projects? Watch this video here..
Don’t have a ton of knowledge about GitLab yet? Don’t worry. We have an extensive onboarding and training program at GitLab and you will be provided with necessary DevOps and GitLab knowledge to fulfil your role.
As a team member responsible for helping to bridge the gap between business and technology, the Analytics Engineer role requires equal amounts business acumen and technical acumen.
- Collaborate with team members to collect business requirements, define successful analytics outcomes, and design data models
- Build trust in all interactions and with Trusted Data Development
- 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
- Create and maintain architecture and systems documentation in the Data Team Handbook
- Maintain the Data Catalog, a scalable resource to support Self-Service and Single-source-of-truth analytics
- Document plans and results in either issue, MRs, the handbook, or READMEs following the GitLab tradition of handbook first!
- Implement the DataOps philosophy in everything you do
- Craft code that meets our internal standards for style, maintainability, and best practices (such as the SQL Style Guide) for a high-scale database environment. Maintain and advocate for these standards through code review.
- 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 in Periscope.
- 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
- 4+ years in the Data space as an analyst, engineer, or equivalent
- 4+ years experience designing, implementing, operating, and extending commercial Kimball enterprise dimensional models
- 4+ years working with a large-scale (1B+ Rows) Data Warehouse, preferably in a cloud environment
- 2+ years experience building reports and dashboards in a data visualization tool
- 1+ years creating project plans to identify tasks, milestones, and deliverables
Also, we know it’s tough, but please try to avoid the confidence gap. You don’t have to match all the listed requirements exactly to be considered for this role.