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BETSOL's open source backup and recovery product line, Zmanda (Zmanda.com), delivers up to 50% savings in total cost of ownership (TCO) and delivers best-in-class performance.

BETSOL Global IT Services (BETSOL.com) builds and supports end-to-end enterprise solutions, reducing time-to-market for customers.

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Job Description

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

Bachelor's degree in Computer Science, Information Systems, Engineering, Finance, Statistics or a related field

Additional Information

UK business hours with overlap till 1 pm EST

Data Engineer Financial Analytics (FP&A)