Senior Financial Data Engineer

Role Overview: Birdeye is seeking a Senior Financial Data Engineer to join their Finance & Accounting organization. In this role, you will play a crucial part in transforming raw transactional signals into clean, trusted, AI-ready schemas that the Finance leadership and C-staff rely on. You will partner directly with Finance Leads to deploy automation, build agentic workflows, ensure data quality, and support analytics engineering. Key Responsibilities: - Data Modeling & dbt Engineering - Develop and maintain the full dbt model layer, transforming transactional data into clean, finance-validated schemas. - Design and enforce a semantic layer for SaaS metrics like ARR, MRR, NRR, and LTV. - Own the 'Revenue Logic' layer to ensure data warehouse revenue matches the General Ledger in NetSuite. - AI Integration & Automation - Collaborate with Finance Lead to deploy Claude Code and Python-based agents for automation. - Build agentic workflows to replace manual analyst tasks and integrate AI tooling for finance automation. - Data Quality & Integrity - Implement automated testing framework using dbt tests and own data quality SLAs for the Finance domain. - Build and maintain data lineage documentation for transparency. - Analytics Engineering & BI Support - Design financial dashboards in Tableau. - Conduct deep-dive SQL analysis and support month-end close activities. - Technical Partnership - Act as a liaison between Finance, Revenue Ops, and Data & Engineering organizations. - Propose automation solutions to reduce manual work in financial reporting. Qualification Required: - AI & Machine Learning for Finance - Agentic Workflow Design - Tech Stack expertise in SQL, Python, and Snowflake - Understanding of SaaS metrics - Data Quality Mindset - AI Tooling experience - Strong communication skills - Education: B.Tech / B.E. in Computer Science or related field (Note: The additional details about the company were not present in the provided job description) Role Overview: Birdeye is seeking a Senior Financial Data Engineer to join their Finance & Accounting organization. In this role, you will play a crucial part in transforming raw transactional signals into clean, trusted, AI-ready schemas that the Finance leadership and C-staff rely on. You will partner directly with Finance Leads to deploy automation, build agentic workflows, ensure data quality, and support analytics engineering. Key Responsibilities: - Data Modeling & dbt Engineering - Develop and maintain the full dbt model layer, transforming transactional data into clean, finance-validated schemas. - Design and enforce a semantic layer for SaaS metrics like ARR, MRR, NRR, and LTV. - Own the 'Revenue Logic' layer to ensure data warehouse revenue matches the General Ledger in NetSuite. - AI Integration & Automation - Collaborate with Finance Lead to deploy Claude Code and Python-based agents for automation. - Build agentic workflows to replace manual analyst tasks and integrate AI tooling for finance automation. - Data Quality & Integrity - Implement automated testing framework using dbt tests and own data quality SLAs for the Finance domain. - Build and maintain data lineage documentation for transparency. - Analytics Engineering & BI Support - Design financial dashboards in Tableau. - Conduct deep-dive SQL analysis and support month-end close activities. - Technical Partnership - Act as a liaison between Finance, Revenue Ops, and Data & Engineering organizations. - Propose automation solutions to reduce manual work in financial reporting. Qualification Required: - AI & Machine Learning for Finance - Agentic Workflow Design - Tech Stack expertise in SQL, Python, and Snowflake - Understanding of SaaS metrics - Data Quality Mindset - AI Tooling experience - Strong communication skills - Education: B.Tech / B.E. in Computer Science or related field (Note: The additional details about the company were not present in the provided job description)