#743 Sr. Data Engineer (Finance Domain)
LatAm 21h ago
Key details
- Location
- LatAm 2
- Work style
- Remote
- Level
- Senior
- Function
- Data & ML
- Focus area
- Data engineering & Analytics
- Posted
- 1h ago
Skills
budgetingbusiness objectsdata governancedata modelingdata structuresdbtexpense managementfinancial reportingforecastingfp&ageneral ledgerjournal entriesnetsuiteprocurementpurchase ordersreconciliationsnowflakesqlworkday
About the role
Senior Data Engineer – Finance & Procurement Analytics
Role Overview
We are seeking an experienced Senior Data Engineer with Finance Domain Expertise to support our Finance and Procurement teams in building and optimizing data models within Snowflake.
The ideal candidate combines strong technical capabilities in Snowflake and dbt with a solid understanding of financial data structures, business processes, and reporting requirements. This role requires someone who can translate Finance and Procurement business needs into scalable, curated data models that support analytics, reporting, and AI-driven insights.
Key Responsibilities
• Design, develop, and maintain curated data models for Finance and Procurement domains using Snowflake and dbt.
• Work with financial data originating from enterprise applications such as NetSuite, Coupa, Brex, Workday Adaptive Planning, or similar platforms.
• Understand and model key financial business objects, including general ledger accounts, journal entries, invoices, purchase orders, vendors, expenses, budgets, and cost centers.
• Collaborate with Finance, Procurement, and business stakeholders to translate functional requirements into reliable, analytics-ready data models.
• Develop and optimize data transformation pipelines, ensuring data accuracy, consistency, quality, and performance.
• Leverage Snowflake Semantic Views and Cortex Agents to enable business-friendly data exploration, self-service analytics, and AI-powered insights.
• Establish data modeling best practices, documentation, testing, and governance across Finance datasets.
Required Qualifications
• Strong hands-on experience with Snowflake, SQL, and dbt, including dimensional modeling and curated analytical data layers.
• Proven experience developing data models for Finance, Accounting, Procurement, or FP&A use cases.
• Understanding of financial data structures, relationships, and business concepts such as GL, AP/AR, budgeting, forecasting, procurement, and expense management.
• Familiarity with data originating from financial applications such as NetSuite, Coupa, Brex, Workday Adaptive Planning, or equivalent enterprise systems.
• Familiarity with Snowflake's AI and analytics capabilities, particularly Semantic Views and Cortex Agents.
• Ability to communicate effectively with both technical teams and nontechnical Finance stakeholders.
Preferred Qualifications
• Experience implementing Snowflake Semantic Views or developing AI-enabled analytics solutions using Cortex.
• Understanding of financial reporting, reconciliation, and data governance requirements.
• Experience integrating financial data from multiple enterprise systems into a unified analytics platform.
• Experience supporting Finance transformation, reporting modernization, or self-service analytics initiatives.
Important Clarification
Direct experience with specific applications such as NetSuite, Coupa, Brex, or Workday Adaptive Planning is not mandatory. What matters most is a strong understanding of financial data, common business objects, their relationships, and how they are used across Finance and Procurement workflows.
Ideal Candidate Profile
A technically strong Snowflake/dbt Data Engineer with practical Finance domain knowledge who can independently design curated financial data models, engage with business stakeholders, and leverage Snowflake's semantic and AI capabilities to deliver actionable business insights.
How well do you match this job?
Skills
Experience
Level
Title
Location
Salary
Freshness
Similarity
Free account needed to apply or save. It takes a minute, and we'll bring you right back to this job.