Data Engineer – Financial Analytics (FP&A)

We are hiring a mid‑level Data Engineer to build the financial data foundation behind executive reporting, working directly with the Head of FP&A on Google BigQuery. The role turns scattered financial and operational data into a single trusted reporting model used by leadership to drive business decisions, reducing manual spreadsheet effort in monthly close and planning cycles.

• Partner with the Head of FP&A to translate business questions into data requirements, metric definitions, and model designs
• Gather data from ERP, CRM, billing, payroll/HR systems, bank feeds, and spreadsheets
• Build and maintain ELT pipelines into BigQuery using SQL, scheduled queries, and orchestration tools (Dataform, dbt, Cloud Composer)
• Cleanse, standardize, and reconcile data, including chart‑of‑accounts mapping, currency conversion, and intercompany eliminations
• Design star and snowflake schemas with conformed dimensions and well‑defined fact tables
• Handle slowly changing dimensions, account hierarchies, fiscal calendars, and actual‑vs‑budget‑vs‑forecast scenarios
• Optimize BigQuery models for cost and performance (partitioning, clustering, materialized views)
• Build a governed semantic layer of financial KPIs and deliver reporting models to executive dashboards in Looker, Looker Studio, Power BI, or Connected Sheets
• Produce Excel‑ready outputs and pivot‑friendly extracts for finance users
• Implement reconciliation checks, apply access controls, maintain a data dictionary, and monitor pipeline health

• 4‑8 years of experience in Data Engineering or Analytics Engineering
• Minimum 2 years of hands‑on experience with Google BigQuery
• Strong experience building data pipelines, dimensional data models, and financial reporting solutions
• Experience working with finance, FP&A, or business analytics teams
• Strong understanding of financial reporting concepts (P&L, balance sheet, cash flow, budget vs actual, forecast variance)
• Expert SQL skills in BigQuery (complex joins, window functions, CTEs, query tuning)
• Advanced Excel skills (Power Query, pivot tables, dynamic arrays)
• Experience integrating data from at least three source systems (ERP, CRM, flat files, APIs)
• Experience with BI tools such as Looker, Looker Studio, or Power BI
• Bachelor’s degree in Computer Science, Information Systems, Engineering, Finance, Statistics or related field