About the job
The Data Team
Join our dynamic data team at Fabulous, where we collaborate cross-functionally to drive data-driven decisions across various business units including Product Growth, User Acquisition, and Finance.
Our team focuses on three primary data domains:
- Data Project Management: We assess business needs, prioritize requests, refine requirements, and maintain open communication with all stakeholders to ensure a transparent feedback loop.
- Applied Analytics & Data Science: Engage in data exploration and define agile analytics approaches, balancing simplicity with complexity where necessary. Each new project incorporates a robust Data Science component during its initial MVP phase.
- Analytics Engineering: We manage data modeling and transformations to build, maintain, and scale our analytics pipelines, focusing on iterative improvement of validated MVPs within our dbt project. Our architecture is designed to manage technical debt effectively, emphasizing thorough testing and data observability.
All team members are expected to excel in at least two of these areas to make impactful contributions autonomously.
We adopt an agile methodology, breaking larger projects into manageable iterations that typically last no more than three weeks to ensure timely impact.
Our modern cloud-based data stack includes Fivetran, BigQuery, dbt, Amplitude, Metabase, and Looker Studio. We are looking to strengthen our team with a skilled Senior Analytics Engineer who can seamlessly integrate into our agile environment and deliver value rapidly.
Expectations | Duties
This role is crucial for the ongoing success of our data science team:
- Collaborate closely with the Head of Data & Analytics to work on projects focused on data modeling and analytics engineering, aimed at enhancing and maintaining our data models and analytics pipelines.
- Contribute to our codebase by building, testing, reviewing, and maintaining robust analytics pipelines using SQL and dbt. Managing technical debt and improving engineering practices are key responsibilities.
- Gradually take ownership of specific areas within the team's responsibilities, influencing how analytics are developed and utilized across business cases.
