Data Engineer – Financial Analytics (FP&A)

Build and maintain end-to-end ELT data pipelines in BigQuery, integrating financial and operational data from ERP, CRM, payroll/HR and spreadsheet sources.

Design and optimize multidimensional financial data models (star and snowflake schemas) to enable executive reporting on key FP&A metrics such as revenue, gross margin, OpEx, budget vs actual variance and cash flow.

Partner closely with Head of FP&A to translate business planning and forecasting needs into documented data requirements, metric definitions, and deliver executive dashboards and finance-ready reporting outputs.

4-8 years of experience in Data Engineering or Analytics Engineering.

Minimum 2 years hands-on experience with Google BigQuery.

Proven skills in building data pipelines, dimensional modeling using Kimball methodology, and financial reporting solutions.

Strong working knowledge of financial reporting concepts including P&L, balance sheet, cash flow, budget vs actuals, and forecast variance analysis.

Experienced in direct collaboration with senior finance stakeholders, able to translate complex finance questions into technical data models and explanations.

Strong expertise in SQL including complex queries, BigQuery-specific optimizations, and dimensional modeling for FP&A use cases.

Background in SaaS, multi-entity, or multi-currency business environments and familiarity with at least one BI tool such as Looker or Power BI.