Business Intelligence (BI) Analytics Intern

Location: San Mateo, CA (Hybrid)

Duration: Summer 2026 (12 weeks)

Compensation: $5K/mo

Reports to: Head of RevOps

Company: Bedrock Data

Data is moving faster than security can keep up, fragmented across clouds, SaaS apps, and AI systems, without the context teams need to protect it. Bedrock Data built the industry's first Metadata Lake to solve this: a living map of all your data that shows what it is, where it lives, who's using it, and how sensitive it is, without ever moving the data itself. This lets enterprises automate security and governance at scale, making data protection continuous and invisible instead of manual and disruptive. Global leaders in technology, finance, healthcare, and biotech trust Bedrock Data to make data security operational. With a $25M Series A led by Greylock, Bedrock is led by repeat founders and technologists who built industry-leading enterprise platforms at Sumo Logic, Rubrik, and Cohesity. Learn more at bedrockdata.ai.

As our BI Analytics Intern, you won't just be pulling data, you will be building the systems that allow our team to understand it. You will play a foundational role in standing up our analytics environment in Salesforce, extracting actionable insights from transcripts, and establishing a source of truth for our internal data assets to ensure our Sales and Finance teams are completely aligned.

• Sales & Forecasting Dashboards: Take the lead on designing and deploying custom analytics within Salesforce. You will establish KPI reporting for pipeline health and sales velocity, and build robust forecasting dashboards to give leadership clear visibility into projected revenue and quota attainment. Audit existing Salesforce data quality and work with stakeholders to clean, normalize, and structure data for reliable reporting

• Finance & RevOps Reporting: Bridge the gap between sales activity and financial performance. You will design finance dashboards in Salesforce to track critical metrics (e.g., ARR, pipeline, and win rates), ensuring the Finance team has real-time access to accurate, reliable data. You will help establish a cadence of automated, self-serve reporting for the Sales and Finance leadership teams

• Transcript & LLM Data Integration: You will analyze LLM-generated transcripts, summaries, and sales call data to uncover trends in buyer sentiment, objection handling, and win/loss drivers.

• Build the Internal Data Repository: Establish and structure an internal knowledge repository. You will document data models and build a data dictionary to ensure our analytics practices are scalable and easily accessible to the rest of the company.

• Cross-Functional Collaboration: Partner directly with Sales, Finance, RevOps, and Product teams to understand their unique data needs and translate business questions into technical requirements.

• Education: Currently pursuing (or recently graduated with) a degree in Business Analytics, Finance, Data Science, Information Systems, Economics, or a related field.

• Business Acumen: A solid understanding of basic sales and financial metrics (pipeline coverage, forecasting, ARR).

• AI Curiosity: A strong interest in Large Language Models (LLMs) and how conversational AI is transforming business intelligence.

• Organizational Skills: A systems-thinker who enjoys building structured documentation and keeping complex information organized.

• Familiarity with Python or R for data manipulation.

• Familiarity in SQL and experience with data visualization tools.

• Prior exposure to Salesforce (or similar CRM platforms); you understand how sales and revenue data is structured (Leads, Opportunities, Accounts).

• Curiosity building foundational analytics.

• High-Impact Projects: You will build revenue and data infrastructure that the company will rely on long after your internship ends.

• Mentorship: Work closely with senior leaders across multiple departments (Sales, Finance, Ops) who are invested in your growth.

• Hands-on AI Experience: Real-world experience analyzing unstructured data using cutting-edge LLM tooling.