Sr. Data Engineer (Finance Domain)
Jobgether
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This role on the market
2,407 open finance roles across 463 companies are on ApplySarthi right now, most of them in Bengaluru (95), Hyderabad (91), Delhi NCR (71).
- Head of Finance (m/w/d)Rotzinger Group
- Finance Transformation ConsultantIBM
- Business Operations & Data Specialist (Finance)Destinusgroup
- Finance ManagerHeidi
- SAP Finance (FI/CO) Migration Architect (m/w/d)Natuvion GmbH
What finance roles keep asking for: Accounting (54%), Excel (29%), SQL (24%), SAP (24%), Stakeholder management (18%), ERP (17%), Financial modelling (15%) — counted across their open postings here.
Remote Data Engineer jobs · Accounting jobs · Data modelling jobs · SQL jobs · Snowflake jobs
Jobgether has 4,170 open roles listed here.
- Account Manager
- Associate Security Architect
- Bilingual (French) Claims Administrator
- Business Development Manager- Quick Commerce
- Content Writer (Project-Based)
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for finance roles keep coming back to Accounting, Excel, SQL, SAP. Practise those questions before you sit with Jobgether.
Questions you are likely to be asked
- Why do you want to join Jobgether?
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- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
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Practise the Sr. Data Engineer (Finance Domain) at Jobgether interview free →Accountabilities:: 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. Nice to Have: 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 work on Finance and Procurement analytics initiatives with meaningful business impact. Exposure to Snowflake’s semantic and AI capabilities, including Cortex Agents. Opportunity to contribute to modern data architecture, financial reporting, and AI-driven analytics solutions.
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Listed on lever · posted 2026-11-13. ApplySarthi collects openings and links to application pages; the role is advertised by Jobgether, not by us.