Finance Analytics Engineer, remote | 1061159

Revel IT
United States
17 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Business Logic Microsoft Azure Software as a Service Cloud Computing Customer Data Management Data Structures Document-Oriented Databases Netsuite SQL Databases Enterprise Data Management Snowflake
+2 more
Git Databricks

Job description

Our client is migrating to a new CRM platform, a change that will significantly impact FP&A’s data models. This Finance Analytics Engineer contract role will sit with FP&A to help migrate and rebuild approximately 150 existing data models to align with the new CRM’s data structure and business logic. This is expected to be a 8 month engagement., * Become familiar with the ~150 existing FP&A data models built on the current CRM data structure

  • Re-map and rebuild data models, transformations, and business logic to align with the new CRM’s schema and data model
  • Partner with FP&A stakeholders to validate that migrated models preserve existing reporting logic, calculations, and KPIs
  • Identify and resolve data discrepancies introduced by the CRM migration, working cross-functionally with IT Enterprise Data, FP&A and ITCS
  • Document data lineage, model logic, and migration decisions to support long-term maintainability
  • Provide regular status updates and risk flags to IT Enterprise Data and FP&A leadership throughout the engagement

Requirements

  • 3-5 years in Finance with analytics focus
  • 3-5 years with financial systems (NetSuite, Adaptive, RevPro, or comparable)
  • SaaS industry experience, * SaaS industry experience
  • 3-5 years in Finance with analytics focus
  • 3-5 years with financial systems (NetSuite, Adaptive, RevPro, or comparable)
  • Experience with cloud platforms (AWS, GCP, or Azure)
  • Expert-level SQL, including data modeling
  • Experience with modern data stack tools (Databricks, Snowflake, dbt, Git, Sigma, or comparable)

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