Sr. Data Engineer (Finance Domain)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Data Engineer (Finance Domain) based in Brazil.

Data Engineer with strong expertise in Snowflake and dbt, combined with practical knowledge of Finance and Procurement operations. In this role, you will design and maintain curated data models that turn complex financial information into reliable, analytics-ready datasets. Working closely with Finance, Procurement, and technical stakeholders, you will translate business requirements into scalable data solutions. You will also contribute to data quality, governance, and modeling standards across financial datasets. By leveraging Snowflake’s semantic and AI capabilities, you will help enable self-service analytics and more actionable, AI-driven business insights.

Responsibilities

• You will take ownership of developing and optimizing data models for Finance and Procurement, ensuring that business users can access consistent, trusted, and meaningful information. Your work will connect technical data engineering practices with real-world financial processes and reporting needs.
• Design, develop, and maintain curated Finance and Procurement data models using Snowflake and dbt.
• Work with financial data from enterprise applications such as NetSuite, Coupa, Brex, Workday Adaptive Planning, or equivalent platforms.
• 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 other business stakeholders to translate functional requirements into reliable, analytics-ready data models.
• Build and optimize data transformation pipelines, ensuring data accuracy, consistency, quality, and performance.
• Leverage Snowflake Semantic Views and Cortex Agents to support business-friendly data exploration, self-service analytics, and AI-powered insights.
• Establish and promote best practices for data modeling, documentation, testing, and governance across Finance datasets.

Requirements

• The ideal candidate combines strong technical data engineering skills with a solid understanding of financial data structures and business processes. You should be comfortable working independently, engaging with nontechnical stakeholders, and translating complex business concepts into scalable data solutions.
• Strong hands-on experience with Snowflake, SQL, and dbt, including dimensional modeling and the development of curated analytical data layers.
• Proven experience building data models for Finance, Accounting, Procurement, or Financial Planning and Analysis (FP&A) use cases.
• Understanding of financial data structures, relationships, and concepts such as general ledger (GL), accounts payable and receivable (AP/AR), budgeting, forecasting, procurement, and expense management.
• Familiarity with data from financial applications such as NetSuite, Coupa, Brex, Workday Adaptive Planning, or equivalent enterprise systems. Direct experience with these specific tools is not mandatory.
• Familiarity with Snowflake’s analytics and AI capabilities, particularly Semantic Views and Cortex Agents.
• Ability to communicate effectively with both technical teams and nontechnical Finance stakeholders.
• Strong problem-solving skills and the ability to independently design reliable, scalable financial data models.
• Opportunity to work on Finance and Procurement analytics initiatives with meaningful business impact.
• Exposure to Snowflake’s semantic and AI capabilities, including Cortex Agents.

Preferred

• 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.

Benefits

• Opportunity to contribute to modern data architecture, financial reporting, and AI-driven analytics solutions.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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