Senior Data Engineer (Finance Domain)
New
B
BlueCloud Services, Inc.Finance analytics
LatAm 2Full-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- SQLSnowflakedbt
Requirements
- Have strong hands-on experience with Snowflake, SQL, and dbt.
- Have experience with dimensional modeling and curated analytical data layers.
- Have developed data models for Finance, Accounting, Procurement, or FP&A use cases.
- Understand financial data structures, relationships, and concepts including GL, AP/AR, budgeting, forecasting, procurement, and expense management.
- Be familiar with data from financial applications such as NetSuite, Coupa, Brex, Workday Adaptive Planning, or equivalent enterprise systems; direct experience with the named applications is not mandatory.
- Be familiar with Snowflake Semantic Views and Cortex Agents.
- Communicate effectively with technical teams and nontechnical Finance stakeholders.
- Preferred: have experience implementing Snowflake Semantic Views or developing AI-enabled analytics solutions using Cortex.
- Preferred: understand financial reporting, reconciliation, and data governance requirements.
- Preferred: have experience integrating financial data from multiple enterprise systems into a unified analytics platform.
- Preferred: have experience supporting Finance transformation, reporting modernization, or self-service analytics initiatives.
Responsibilities
- Design, develop, and maintain curated data models for Finance and Procurement using Snowflake and dbt.
- Work with financial data from enterprise applications such as NetSuite, Coupa, Brex, and Workday Adaptive Planning or similar platforms.
- Model 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 analytics-ready data models.
- Develop and optimize data transformation pipelines for accuracy, consistency, quality, and performance.
- Use Snowflake Semantic Views and Cortex Agents to support business-friendly data exploration, self-service analytics, and AI-powered insights.
- Establish data modeling best practices, documentation, testing, and governance across Finance datasets.
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