Analytics Engineer

Job summary

The role focuses on building and maintaining the data modeling layer for product intelligence, ensuring data is trustworthy and self-serve. The position involves migrating analytics stacks and implementing tracking and experimentation foundations.

Qualifications

• Proficient in SQL and dbt, with experience owning data models end to end.
• Familiarity with event-based tracking tools such as Segment or Amplitude.
• Experience with Git-based development workflows.
• Strong communication skills for explaining data definitions to various stakeholders.
• Regular use of AI tools in coding and workflow.
• Ability to navigate ambiguity and refactor legacy systems.

Responsibilities

• Develop and maintain dbt models in the new Analytics Warehouse.
• Implement and QA tracking plans in Segment and Amplitude.
• Support experimentation by structuring assignment and outcome data.
• Define and document metrics in the semantic layer for consistency.
• Utilize AI-augmented practices in data modeling.
• Collaborate with Product Managers and Analysts to create reusable data models.
• Ensure data quality through tests and monitoring.

Education

• Relevant experience in data engineering or analytics roles.

Tools

• Data Warehouse: GCP / BigQuery
• Transformation: dbt
• Orchestration: Airflow
• Tracking: Segment, Amplitude
• BI: Omni