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Mid-level BI generalist with modern stack attracts moderate applicant volume despite smaller company.
BI and data engineering skills are highly transferable across industries.
Multiple mandatory technical skills (dbt, cloud warehouse, BI tools, SQL, Python) but no strict years requirement.
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Design and maintain scalable cloud data models (Star/Snowflake Schema) and data pipelines with 99.9% uptime for critical dashboards.
Develop and manage semantic layers to ensure consistent business logic across the organization using dbt and collaborate with AI engineers for conversational BI implementations.
Create automated, impactful visualizations and translate complex business requirements into user-friendly dashboards and conversational BI solutions.
Strong SQL skills with ability to write and optimize complex queries.
Experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake/BigQuery/Redshift).
Expert-level proficiency with BI tools such as Power BI, Tableau, or Looker.
Python scripting experience, especially for data manipulation and integration with NLP/LLM workflows. Work Experience Required: Not explicitly mentioned in the JD.
Operates effectively as a "data translator" capable of explaining technical concepts to non-technical stakeholders, especially marketing teams.
Has troubleshooting skills to diagnose root causes of data/reporting issues beyond superficial fixes.
Demonstrates curiosity and capability in shifting BI towards AI-driven, conversational data insights, including familiarity with NLQ and vector databases or RAG frameworks.