Data Engineer – Financial Analytics (FP&A)

About the Role

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. This role turns scattered financial and operational data into a single trusted reporting model that leadership uses to run the business. You will act as the technical partner to the Head of FP&A translating planning forecasting and performance questions into well-designed data models and repeatable metrics. You will own the path from source systems to executive dashboards: gathering data from ERP CRM billing HR and spreadsheet sources modeling it in BigQuery and delivering metrics such as revenue gross margin operating expense budget-versus-actual variance and cash position. The aim is to reduce manual spreadsheet effort in monthly close and planning cycles and to give leadership faster consistent answers.

Responsibilities

Partnering with FP&A

• Work day to day with the Head of FP&A to understand reporting needs across budgeting forecasting month-end close and board reporting.
• Translate business questions into data requirements metric definitions and model designs and document them clearly.
• Support planning cycles with timely reconciled data and ad hoc analysis for leadership requests.

Data integration and transformation

• Gather data from multiple sources such as ERP CRM billing payroll/HR systems bank feeds and Excel or Google Sheets workbooks.
• Build and maintain ELT pipelines into BigQuery using SQL scheduled queries and orchestration tools (for example Dataform dbt or Cloud Composer).
• Cleanse standardize and reconcile data including chart-of-accounts mapping currency conversion and intercompany eliminations.

Multidimensional data modeling

• Design star and snowflake schemas with conformed dimensions (time entity account cost center product customer region) and well-defined fact tables.
• Handle slowly changing dimensions account hierarchies fiscal calendars and actuals-versus-budget-versus-forecast scenarios.
• Optimize BigQuery models for cost and performance through partitioning clustering and materialized views.

Financial metrics and reporting

• Build a governed semantic layer of financial KPIs: revenue ARR/MRR where relevant gross margin EBITDA OpEx by function headcount cost cash flow and variance analysis.
• Deliver reporting models that feed executive dashboards in Looker Looker Studio Power BI or Connected Sheets.
• Produce Excel-ready outputs and pivot-friendly extracts for finance users who work in spreadsheets.

Data quality and governance

• Implement reconciliation checks between source systems the general ledger and reported figures.
• Apply access controls appropriate to sensitive financial data and maintain a data dictionary for every published metric.
• Monitor pipeline health and resolve data issues before they reach leadership reports.

Looking For

• 4-8 years of experience in Data Engineering or Analytics Engineering.
• Minimum 2 years of hands-on experience working 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 such as P&L Balance Sheet Cash Flow Budget vs Actuals and Forecast Variance analysis. 

Mandatory Skills

Technical Skills

• Expert SQL: complex joins window functions CTEs aggregations query tuning and BigQuery-specific features (partitioning clustering nested and repeated fields scheduled queries).
• Proven experience designing multidimensional (dimensional) data models using Kimball methodology: facts dimensions hierarchies and slowly changing dimensions.
• Advanced Excel: Power Query pivot tables XLOOKUP/INDEX-MATCH dynamic arrays and building finance-ready reporting templates.
• Hands-on experience integrating data from at least three types of source systems (for example ERP CRM flat files APIs).
• Working knowledge of financial statements and FP&A concepts: P&L balance sheet cash flow chart of accounts budget-versus-actual and forecast variance.
• Experience with at least one BI tool such as Looker Looker Studio or Power BI.
• Clear communicator who can explain data logic to finance leaders and document metric definitions precisely.

Soft Skills

• Strong analytical and problem-solving skills
• Ability to work directly with senior finance stakeholders
• Clear communicator who can explain data logic to finance leaders and document metric definitions precisely.
• Stakeholder management and business partnering capability
• Ability to translate business requirements into technical solutions

Good to Have Skills

• Experience with dbt or Dataform for version-controlled tested SQL transformations.
• Familiarity with LookML or a comparable semantic modeling layer.
• Exposure to ERP finance modules (for example NetSuite SAP Oracle or Microsoft Dynamics) and planning tools (for example Anaplan Adaptive Planning or Pigment).
• Python for data processing API ingestion or automation.
• Experience with Git CI/CD and Google Cloud services such as Cloud Storage Cloud Functions and Cloud Composer.
• Google Cloud Professional Data Engineer certification.
• Prior work in a SaaS IT services or multi-entity multi-currency business

Qualifications :

Bachelors degree in Computer Science Information Systems Engineering Finance Statistics or a related field

Additional Information :

UK business hours with overlap till 1 pm EST

Remote Work :

No

Employment Type :

Full-time