Senior Financial Data Engineer

About Birdeye
Birdeye is the leading agentic marketing platform for multi-location brands.

Companies like H&R Block, Aspen Dental, and Caesars Entertainment use Birdeye to manage marketing across thousands of locations — from how they get found, to how they convert, to how they retain customers. Our platform replaces disconnected point tools with AI agents that execute work at the location level — responding to reviews, updating listings, publishing content, and driving conversions.

Backed by Marc Benioff, Jerry Yang, and Accel-KKR, Birdeye was named to G2’s 2026 Best Agentic AI Products list — appearing alongside the world’s leading AI companies. We’re expanding rapidly into enterprise, with growing adoption across large, multi-location brands.

About The Role

Birdeye's Finance & Accounting organization is scaling fast — and so is the complexity of its data. We are looking for a Senior Financial Data Engineer who will become the technical backbone of our global finance team.

This is not a traditional data engineering role. It is not a pure finance role either. It is a builder role for someone who understands that a broken model at 3 AM can delay month-end close — and who takes that personally. You sit at the intersection of revenue data, SaaS metrics, and AI automation, transforming raw transactional signals from Salesforce, Recurly, and NetSuite into the clean, trusted, AI-ready schemas that the Finance leadership and C-staff relies on.

You will partner directly with the Finance Leads to deploy Claude Code-powered agents, automate reconciliations, and eliminate manual variance analysis. This is a high-ownership, high-visibility role with a direct line to senior leadership.

Key Responsibilities

1. Data Modeling & dbt Engineering

• Develop and maintain the full dbt model layer — from raw staging to marts — transforming messy transactional data into clean, finance-validated schemas.
• Design and enforce a semantic layer for SaaS metrics: ARR, MRR, NRR, GRR, Churn, Expansion, and LTV.
• Implement dbt best practices: modular design, ref() usage, incremental models, exposures, and a well-documented DAG.
• Own the 'Revenue Logic' layer — ensuring the data warehouse definition of recognized revenue matches the General Ledger in NetSuite at every grain.

2. AI Integration & Automation

• Collaborate with the Finance Lead to deploy Claude Code and Python-based agents that automate complex reconciliations, variance analysis, and anomaly detection.
• Build agentic workflows that replace manual analyst tasks: auto-generating commentary on revenue movements, flagging suspicious transactions, and summarizing period-over-period shifts.
• Integrate LLM-powered tooling into data pipelines to enrich financial data with natural language context and classification.
• Evaluate and adopt emerging AI tooling (vector databases, RAG pipelines, fine-tuning) to enhance finance automation use cases.

3. Data Quality & Integrity

• Implement a comprehensive automated testing framework using dbt tests to validate business logic.
• Own data quality SLAs for the Finance domain: define acceptance thresholds, track quality scores, and report to stakeholders.
• Build and maintain data lineage documentation so the Finance team always knows the provenance of every number.

4. Analytics Engineering & BI Support

• Partner with FP&A and Accounting to design executive-ready financial dashboards in Tableau or similar BI tools.
• Perform deep-dive SQL analysis in Snowflake to diagnose and resolve discrepancies between upstream CRM data and downstream financial reports.
• Act as the technical data SPOC for month-end close support, audit data requests, and ad hoc finance queries.

5. Technical Partnership

• Serve as the data engineering liaison between Finance, Revenue Ops, and the broader Data & Engineering organizations.
• Translate complex financial requirements (GAAP treatment, recognition schedules, deferred revenue) into precise technical specifications.
• Identify bottlenecks in the financial reporting cycle and propose automation solutions that reduce close time and eliminate manual reconciliation work.