Own, maintain, and improve core data systems including dbt, Stitch, and the BigQuery data warehouse sourced from NoSQL datasets (e.g., Firestore).
Develop reliable, well-documented data models, transformations, and ELT pipelines supporting revenue, operational, and financial reporting.
Implement and maintain data quality and observability frameworks, including dbt tests, schema-change monitoring, and pipeline alerts.
Be the BigQuery expert to apply version control, documentation, naming conventions, and workflow best practices for long-term maintainability.
Build, maintain, and optimize Google Looker Studio dashboards, ensuring accuracy and usability.
Perform ongoing dashboard maintenance, enhancements, and metric updates as business needs evolve.
Build and maintain recurring operational reports, including those used for enterprise customer audits and sales pipelines.
Partner closely with Finance, Operations, and Customer-facing teams to translate business needs into actionable analytics and data workflows.

2–3 years of hands-on experience in data analysis or analytics engineering.
Strong SQL skills and proficiency with dbt and BigQuery.
Experience with ETL tools (Stitch or similar) and NoSQL datastores (e.g., Firestore).
Demonstrated experience building and maintaining dashboards in Google Looker Studio or comparable BI tools.
Experience supporting revenue, financial, or compensation-impacting analytics.
Ability to own end-to-end analytics work end-to-end, from raw data to stakeholder-facing outputs.
Strong attention to detail, data accuracy and QA.
Comfortable managing and communicating on multiple priorities.

Business Intelligence Engineer

Key skills