Data Engineering Internship at Auditoria.AI – Santa Clara, California

About Us
We're an AI-driven SaaS automation provider for corporate finance that automates back-office business processes involving tasks, analytics, and responses in Accounts Payable and Accounts Receivable. By leveraging natural language processing, artificial intelligence, and machine learning, based on proprietary small language models and commercial LLMs, Auditoria removes friction and repetition from mundane tasks while automating complex functions and providing real-time visibility into cash performance. Corporate finance and accounting teams use Auditoria to accelerate business value while minimizing heavy IT involvement, improving business resilience, lowering attrition, and accelerating business insights.
Founded in 2019 and backed by KPMG, Workday Ventures, Dell Technologies, Venrock, Innovius Capital, Sentinel Global, NeoTribe Ventures, Engineering Capital, and Firebolt Ventures, we build AI Team Mates that drive intelligent automation by combining fine-grained analytical orchestration of a company's typical financial and audit workflows with conversational AI, delivering rapid value to the finance/audit back office.
We've received numerous awards including:

• Best AI-Powered Financial Automation Solution of 2026 by Acquisition International Magazine’s Global Excellence Awards.
• CBInsights Fintech 100 - 2025.
• Global Excellence Awards - Best AI-Driven Finance Automation Platform - 2025 Winner.
• Q3 2024 Constellation ShortList™ for AI-Driven Cognitive Applications for the fifth year in a row.
• The Gartner Emerging Tech Impact Radar: Artificial Intelligence Report 2024 named Auditoria as a sample vendor for Composite AI.
• Named a sample vendor for intelligent applications in finance in the Hype Cycle for Autonomous Accounting, 2024, the Hype Cycle for Finance AI and Advanced Analytics, 2024, and the Hype Cycle for the Future of Enterprise Applications, 2024 reports.

About the RoleWe're scaling an AI-native enterprise SaaS platform that powers agentic automation for corporate finance teams at Fortune 500 companies. As a Data Engineering Intern, you'll build the data infrastructure that makes our agents work. Clean, well-modeled, LLM-ready data flowing from customer ERPs into Snowflake, through our semantic layer, and into the retrieval pipelines that ground every decision our agents make.
You'll work across the modern data stack and implement medallion architecture patterns that serve both operational systems and AI/ML workloads.
Key Responsibilities

• Building ingestion pipelines from customer ERPs and finance systems into data warehouse
• Writing transformations in our Bronze, Silver, Gold medallion architecture, with an eye toward making data LLM-ready: well-named, well-typed, well-documented, and semantically meaningful
• Extending the semantic layer that powers natural-language analytics, this is what lets non-technical finance users ask questions and get grounded answers
• Preparing and structuring data for retrieval, embeddings, vector search, and context assembly for RAG pipelines that feed our agents
• Implementing data quality checks, lineage, and monitoring so agents never act on bad data
• Tuning queries and warehouse usage for both cost and latency
• Contributing to technical documentation and participating in code reviews

Qualifications

• Pursuing (or recently graduated) a Bachelor's or Master's in Computer Science, Data Engineering, Statistics, or a related field
• Solid SQL skills: joins, window functions, and a basic grasp of how to read a query plan
• Hands-on experience with at least one relational database (MySQL, Postgres, or similar) through coursework, projects, or prior internships
• Comfortable writing Python for data processing and scripting
• Genuine interest in LLMs and AI systems, you've played with OpenAI/Anthropic APIs, built a RAG project, or thought seriously about how data shape affects model behavior
• Excellent communication, you can explain what you built and why

Preferred Qualifications

• Exposure to Snowflake, BigQuery, or Databricks
• Experience with dbt, Airflow, or another orchestration/transformation tool
• Experience with vector databases (Pinecone, Weaviate, pgvector, Snowflake Cortex Search) or embedding workflows
• Understanding of dimensional modeling (star/snowflake schemas)
• Any prior internship or substantive personal project in data engineering
• Authorized to work in the United States without the need for future sponsorship