✨ About The Role
- The role involves transforming raw data into usable tables to support self-serve data artifacts and analytics use cases.
- The candidate will collaborate with Data Engineering, Product Engineering, and Data Infrastructure teams to define data infrastructure needs.
- The position requires applying software engineering best practices within the analytics workflow, including version control and testing.
- The successful candidate will improve data availability and quality, ensuring reliable access for the business.
- The role includes implementing exploration tools and dashboards for cross-functional stakeholders to gain insights.
- The candidate will deliver insights through ad hoc analyses and data extractions to address important business needs.
- Identifying process improvements and contributing to documentation will be part of the responsibilities.
⚡ Requirements
- The ideal candidate will have over 5 years of professional experience in analytics engineering, data analysis, or related fields.
- Strong expertise in SQL is essential for transforming raw data into usable formats for analytics.
- Experience with data infrastructure and data modeling is crucial, particularly with tools like Looker.
- The candidate should possess excellent communication skills to convey technical concepts to non-technical stakeholders.
- A strong business acumen and product intuition will help in understanding and addressing business needs effectively.
- Familiarity with software tools such as GitHub, Rudderstack, and BigQuery is preferred but not mandatory.
- The successful candidate will be self-motivated, ambitious, and able to work independently in a remote environment.