We are seeking a motivated AI Intern to join the Data & AI Agent team and help build the data ... Familiarity with the modern data stack (dbt, a columnar warehouse such as StarRocks/Snowflake ...
We are seeking a motivated AI Intern to join the Data & AI Agent team and help build the data ... Familiarity with the modern data stack (dbt, a columnar warehouse such as StarRocks/Snowflake ...
Experience working with modern data platforms like Teradata, Snowflake, and Databricks * Passion for staying current with AI research, especially in the areas of reasoning, planning, and autonomous ...
Experience working with modern data platforms like Teradata, Snowflake, and Databricks * Passion for staying current with AI research, especially in the areas of reasoning, planning, and autonomous ...
Snowflake Intern information
See Oregon salary details
$9.40 - $10.88
3% of jobs
$10.88 - $12.36
3% of jobs
$12.36 - $13.84
3% of jobs
$13.84 - $15.32
9% of jobs
$15.80 is the 25th percentile. Wages below this are outliers.
$15.32 - $16.80
21% of jobs
The median wage is $17.41 / hr.
$16.80 - $18.28
26% of jobs
$19.45 is the 75th percentile. Wages above this are outliers.
$18.28 - $19.75
13% of jobs
$19.75 - $21.23
12% of jobs
$21.23 - $22.71
4% of jobs
$22.71 - $24.19
3% of jobs
$24.19 - $25.67
3% of jobs
$9
$18
$25
How much do snowflake intern jobs pay per hour?
As of Jun 9, 2026, the average hourly pay for snowflake intern in Oregon is $18.01, according to ZipRecruiter salary data. Most workers in this role earn between $15.24 and $20.34 per hour, depending on experience, location, and employer.
What types of projects can a Snowflake Intern expect to work on, and how do these projects support professional development?
As a Snowflake Intern, you can expect to work on a variety of projects such as developing data pipelines, optimizing SQL queries, supporting data migration efforts, and assisting with cloud data warehouse integrations. These projects are typically designed to provide hands-on experience with Snowflake's platform and related cloud technologies, allowing interns to build practical technical skills. You'll often collaborate with experienced engineers and data analysts, gaining insight into real-world data engineering workflows and best practices. This exposure not only enhances your technical toolkit but also helps you understand the collaborative dynamics of data teams, positioning you well for future roles in data engineering or analytics.
What are the key skills and qualifications needed to thrive as a Snowflake Intern, and why are they important?
To thrive as a Snowflake Intern, you should have a solid understanding of SQL, data warehousing concepts, and programming languages such as Python or Java, often supported by ongoing coursework in computer science or a related field. Familiarity with the Snowflake platform, cloud services like AWS or Azure, and data analytics tools is highly beneficial. Strong problem-solving, attention to detail, and effective communication skills help you collaborate and learn quickly in a team environment. These competencies are vital to contribute meaningfully to projects and adapt to the fast-paced, data-driven work at Snowflake.
What is the difference between Snowflake Intern vs Snowflake Developer?
| Aspect | Snowflake Intern | Snowflake Developer |
|---|---|---|
| Required Credentials | Basic understanding of cloud data platforms, possibly some coursework or certifications | Proficiency in SQL, data warehousing, and Snowflake-specific features, often with relevant certifications |
| Work Environment | Internship setting, learning-focused, entry-level tasks | Full-time role, development-focused, responsible for building and maintaining Snowflake data solutions |
| Employer & Industry Usage | Internships in tech companies, data teams, or consulting firms | Data engineering teams across various industries using Snowflake for data management |
The main difference between a Snowflake Intern and a Snowflake Developer lies in experience, responsibilities, and skill level. Interns are typically in learning roles with entry-level tasks, while developers are responsible for designing and implementing Snowflake data solutions, requiring more expertise and certifications.
What does a Snowflake Intern do?
A Snowflake Intern typically works on projects related to data warehousing, cloud computing, and software engineering using the Snowflake platform. Interns may assist with building data pipelines, optimizing queries, or developing new features under the guidance of experienced engineers. The internship provides hands-on experience with real-world data challenges and exposure to modern cloud technologies. Interns are encouraged to learn, collaborate, and contribute to the team’s goals while gaining insights into the industry.
What are the most commonly searched types of Snowflake jobs in Oregon? The most popular types of Snowflake jobs in Oregon are:
What are popular job titles related to Snowflake Intern jobs in Oregon? For Snowflake Intern jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Snowflake Intern jobs in Oregon look for? The top searched job categories for Snowflake Intern jobs in Oregon are:
What cities in Oregon are hiring for Snowflake Intern jobs? Cities in Oregon with the most Snowflake Intern job openings:
Job description
About the role:
We are seeking a motivated AI Intern to join the Data & AI Agent team and help build the data infrastructure, AI agents, and automated workflows that power Armada's go-to-market motion. This is a hands-on role focused on data engineering and applied AI - not traditional ML research. You'll work directly with the Head of Data and AI Agent on the systems that turn fragmented Salesforce, SharePoint, and operational data into a single source of truth, and on the AI-powered tooling (lead scoring, signal intelligence, internal copilots) that runs on top of it.
We are seeking a motivated Intern (unpaid) to join our team. This unpaid internship program is tailored for engineering students seeking to enrich their academic learning with practical, hands-on experience in the field.
Location: This role is remote.
Key Responsibilities:
- Build and maintain data pipelines across Salesforce, SharePoint, Excel, and operational systems into our StarRocks data warehouse using dbt and Python.
- Develop and ship AI agents and copilots using the Claude API (and other LLM tooling) for use cases like lead scoring, account research, call analysis, and internal Q&A over company data.
- Design and automate cross-system workflows using Power Automate, Teams Adaptive Cards, and lightweight Python/FastAPI services to replace manual, spreadsheet-driven processes.
- Model business data in dbt and Omni - building reusable semantic models, metrics, and dashboards that GTM, RevOps, and leadership rely on.
- Enrich and clean prospect and account data using sources like ZoomInfo, LinkedIn Sales Navigator, and public government datasets (e.g., USASpending, SAM.gov, FCC, EIA, FERC, SEC EDGAR).
- Prototype and ship internal tools end-to-end - backend (Python/FastAPI), frontend (Vite/React), and storage (PostgreSQL, StarRocks) - for AI-prioritized daily workflows.
- Write clear documentation for data models, pipelines, agents, and workflows so the team can extend and maintain them.
- Collaborate with GTM, RevOps, Finance, and product teams to translate business questions into data and automation solutions.
- Stay current on advances in agentic AI, retrieval, evals, and the modern data stack - and bring useful ideas back to the team.
Qualifications:
- Pursuing or recently completed a degree in Computer Science, Data Science, Data Engineering, Information Systems, Analytics, or a related field.
- Strong Python skills, including experience with libraries like Pandas, requests, and FastAPI or Flask.
- Solid SQL skills - able to write and debug analytical queries (joins, window functions, CTEs) against real-world, messy data.
- Familiarity with the modern data stack (dbt, a columnar warehouse such as StarRocks/Snowflake/BigQuery/Databricks, and a BI tool such as Omni, Tableau, Looker, or Power BI).
- Hands-on experience building something with an LLM API (Claude, OpenAI, etc.) - even a side project counts. Familiarity with prompt design, tool/function calling, or RAG is a strong plus.
- Exposure to workflow automation tools (Power Automate, Zapier, n8n, Airflow, or similar).
- Comfort with Git and basic software engineering practices (branches, PRs, code reviews).
- Strong problem-solving and analytical skills; able to work independently and in a team-oriented environment.
What You'll Gain:
- Hands-on experience working with modern AI, automation, and data engineering tools in a real-world business environment
- Exposure to cutting-edge technologies including LLMs, workflow automation, and cloud data platforms
- The opportunity to build impactful projects used by GTM, RevOps, Finance, and leadership teams
- Mentorship and collaboration with experienced engineers and business leaders
- Practical experience with Python, SQL, dbt, APIs, dashboards, and AI-powered workflows
- A stronger technical portfolio and resume through meaningful, production-focused projects
- Insight into how AI and data systems drive decision-making and operational efficiency in a fast-growing technology company
- Professional development in problem-solving, communication, collaboration, and cross-functional teamwork
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About ArmadaGlobal
Sourced by ZipRecruiter
Company size
51 - 200 Employees
Headquarters location
Hunt Valley, MD, US
Year founded
2004