Analytics Engineering at GitLab

The mission of the Analytics Engineering team is to maximize the impact of business decisions and strategy with data solutions that are trusted and scalable.

We do this by helping all GitLab teams move up the Data maturity by means of our GitLab values and our Data Team Principles.

Analytics Engineering Responsibilities

The Analytics Engineering Team is directly responsible for:

• Integrating and conforming data from 50+ sources into a single analytics platform
• Encoding business logic into dbt data models that support enterprise-grade reporting and analytics

Additionally, the Analytics Engineering Team supports the following responsibilities

• With Data Leadership:
  • Define and publish a Data Strategy to help maximize the value of GitLab’s Data Assets
  • Broadcast regular updates about data deliverables, ongoing initiatives, and upcoming plans
• With the Data Platform Team:
  • Build and maintain the company’s central Enterprise Data Warehouse to support Reporting, Analysis, Dimensional Modeling, and Data Development for all functional teams
• With the Data Governance and Quality Team:
  • Help define and champion Data Quality practices and programs for GitLab data systems
• With the Data Science and Enterprise Analytics Team:
  • Provide Self-Service Data capabilities to help everyone leverage data and analytics

Analytics Engineering Organization

The Analytics Engineering Organization is composed of sub-teams as follows:

• GTM Analytics Engineering
• R&D Analytics Engineering
• Finance Analytics Engineering
• People Analytics Engineering

Analytics Engineering Ceremonies

Each sub-team has the following ceremonies. They can be at a cadence that makes sense for the sub-team and can also use asynchronous or synchronous approaches as agreed upon by the sub-team. It is optional for team members to attend the ceremonies of other pillars. Team members are encouraged to attend other pillar ceremonies where attendance adds value.

• Backlog Refinement Sync
• Iteration Planning Sync
• Sub-Team Meeting
• Analytics Engineering Functional Team Sync (All Sub-Teams Attend)

Analytics Engineering Processes

• Triage follows the Enterprise Data Team Triage Process. This is the primary intake process for P1-Ops issues.

Analytics Engineering Leadership Roles

• The Manager, Data provides leadership to the sub-teams as described in the Senior Manager, Data Job Family

• Lead Analytics Engineer (Stable Counterpart for the Business)

  • The Lead Analytics Engineer fulfills the below responsibilities from the Senior Analytics Engineer Job Responsibilities:
  • Own one or more stakeholder relationship in Go To Market, Research & Development, General & Administrative, Financial Analytics, or Engineering Analytics business functions.
  • Co-DRI of Key Results along with the Manager, Data.
  • Lead work breakdown sessions for OKRs.
  • Work with functional stakeholders to prioritize P3-Other issues.
  • Serve as a primary or back-up Maintainer on the Data Team Project. Provide final review, feedback, and approval of Merge Requests.
  • Review the weekly stand-up and provide support as needed to unblock team members and answer questions.