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Mid-level data analyst, hybrid metro role, broad in-demand stack increases applicant density.
Strong finance/CFO domain focus reduces cross-industry transferability.
Multiple mandatory technical and finance domain skills required, raising screening rigidity.
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Own design and implementation of data warehouse and data mesh solutions using star schema/facts and dimensions in platforms like Snowflake, dbt, and Databricks.
Develop reusable, governed, and audit-ready finance data products supporting financial data management.
Build advanced Business Intelligence solutions including visualization, reports, dashboards, and custom AI-driven BI capabilities across multiple BI tools for actionable insights.
Strong experience in data warehouse and data mesh design using star schema/facts and dimensions with tools such as Snowflake, dbt, Databricks.
Expertise in financial data management including building governed and audit-ready finance data products.
Advanced skills in BI tools like Power BI, Looker, Tableau with narrative storytelling and analytics capabilities.
Work Experience Required: Not explicitly mentioned in the JD.
Candidate with proven ability to design and implement complex BI and data warehouse solutions in financial domains such as finance, accounting, FP&A, or controller functions.
Experience working with AI integration in BI tools leveraging Agentic AI platforms like Snowflake Cortex AI, Semantic Layers, or MCP.
Experience or aspiration to work with platforms such as NSAW, Boomi Data Hub, or Salesforce Data Cloud is favorable.