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Metadata Internship information

What is a metadata internship?

A Metadata Internship is a training position where interns assist with organizing, categorizing, and managing metadata for digital or physical assets. Metadata refers to the descriptive information about data, such as tags, keywords, descriptions, and classifications that improve accessibility and retrieval. Interns may work with databases, content management systems, or digital libraries to ensure metadata accuracy and consistency. This role is common in industries like media, publishing, libraries, and technology, where proper data organization is crucial. It's an excellent opportunity to gain hands-on experience in data management, digital archiving, and information science.

What types of projects or tasks can I expect to work on during a metadata internship?

As a Metadata Intern, you will typically assist with organizing, cataloging, and updating digital assets or records using established metadata standards. Your day-to-day tasks may include reviewing datasets for accuracy, entering descriptive information into databases, and collaborating with team members on data cleanup or migration projects. You might also support quality assurance efforts and participate in meetings about optimizing metadata workflows. This hands-on experience will help you develop technical skills and gain a deeper understanding of how structured data supports larger organizational needs.

What are the key skills and qualifications needed to thrive in a metadata internship, and why are they important?

To thrive as a Metadata Internship, you need strong organizational skills, attention to detail, and familiarity with data management principles, often supported by coursework in information science or library studies. Knowledge of metadata standards (such as Dublin Core, MARC), experience with database management systems, and proficiency in tools like Excel or specialized content management systems are valuable. Effective communication, critical thinking, and a collaborative mindset help interns excel in team-based projects and resolve data-related challenges. These skills are important for accurately categorizing, managing, and maintaining the quality and accessibility of digital information—a core function in many organizations.

What are the most commonly searched types of Metadata jobs in California?

The most popular types of Metadata jobs in California are:

What are popular job titles related to Metadata Internship jobs in California?

For Metadata Internship jobs in California, the most frequently searched job titles are:

What cities in California are hiring for Metadata Internship jobs?

Cities in California with the most Metadata Internship job openings:

Infographic showing various Metadata Internship job openings in California as of August 2026, with employment types broken down into 13% Internship, 25% Full Time, 49% Part Time, and 13% Temporary. Highlights an 100% In-person job distribution.

Campus Undergraduate Summer Internship Program - 2027 Data Analytics, Enterprise Technology Services

American Express

Palo Alto, CA • On-site

$24.05/hr

Full-time

Posted 4 days ago


American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

25th of 154 rated financial services


Job description


Business Unit / Role Specific Info
The Enterprise Technology Services organization partners with every part of the American Express business to power the company's growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company's technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
At American Express, we empower future data professionals to learn, innovate, and make an impact from day one. As a Data and Analytics Intern in Enterprise Technology Services, you will join a 10 week Summer Internship Program and support analytics work that helps technology teams make informed decisions across governance, architecture, modeling, data science, and emerging technology initiatives.
This role is designed for students interested in using data, analytics, financial insight, modeling, AI, or quantitative methods to solve business and technology problems. Depending on team alignment, you may work with technology business enablement, governance, model focused teams, enterprise business data architecture, data science teams, or quantum computing exploration efforts.
Potential Focus Areas
American Express Data and Analytics Interns may be aligned to different technology teams based on business needs, project requirements, and individual strengths. Experience in one or more of the following areas is beneficial:
  • Technology Business Enablement: portfolio analysis, financial management, delivery analytics, resource insights, operating rhythm materials, executive reporting, or business performance analysis.
  • Actuarial, Modeling, and AI Governance Analytics: quantitative analysis, actuarial methods, model documentation, model output review, scenario analysis, model governance, AI oversight, or responsible AI concepts.
  • Enterprise Business Data Architecture: data requirements and data-source analysis, source-to-target mapping, metadata and lineage, data quality and controls, data governance and standards, and foundational enterprise data architecture concepts.
  • Data Science: Python, R, SQL, exploratory analysis, statistical analysis, predictive modeling fundamentals, evaluation metrics, feature review, visualization, or insight generation.
  • Quantum Computing Exploration: Quantum computing fundamentals, emerging technology research, use case evaluation, experimentation documentation, technical landscape analysis, or early stage analytics.
  • Core Skills Across All Areas: analytical thinking, attention to detail, communication, collaboration, intellectual curiosity, responsible use of data and AI, and ability to explain insights to technical and non technical audiences.

Responsibilities
Responsibilities and What Type of Work to Expect
  • Collect, clean, validate, and organize data from technology, portfolio, financial, operational, architectural, or modeling sources to support analysis and reporting.
  • Support data requirements, source-to-target mapping, metadata and lineage documentation, and data quality checks or control validation for assigned projects.
  • Analyze datasets to identify trends, anomalies, opportunities, risks, and insights relevant to technology and business decision making.
  • Support dashboards, key performance indicators, governance reports, executive summaries, and stakeholder ready presentations.
  • Assist with financial, statistical, quantitative, exploratory, or scenario based analyses based on team placement and project needs.
  • Document assumptions, data sources, requirements, mappings, calculations, methodology, metadata, lineage, data quality and control considerations, and analytical outputs to support transparency, traceability, and reproducibility.
  • Partner with technology, product, finance, architecture, risk, data science, and business stakeholders to understand requirements and translate them into clear analytical outputs.
  • Use AI enabled analytics, productivity, and reporting tools to support research, summarization, data exploration, and workflow efficiency while validating outputs before use.
  • Communicate findings clearly to technical and non technical audiences through written summaries, presentations, dashboards, or discussion materials.

Qualifications
Minimum Qualifications
  • Currently enrolled in a full time Bachelor's degree program in Business Administration, Finance, Economics, Mathematics, Statistics, Actuarial Science, Data Analytics, Information Systems, Computer Science, Engineering, or a related discipline.
  • Interest in one or more areas such as data analytics, technology business enablement, data architecture, actuarial analytics, model governance, data science, AI, quantum computing, or business intelligence.
  • Foundational knowledge of data analytics concepts, including data collection, validation, analysis, visualization, interpretation, and insight generation.
  • Foundational understanding of financial analysis, statistics, quantitative analysis, risk analysis, data modeling, or business performance measurement.
  • Awareness of Software Development Lifecycle, Agile methodology, data governance, or technology delivery concepts.
  • Foundational understanding of Generative AI concepts, responsible use, prompt based workflows, and human validation of AI generated outputs.
  • Strong analytical thinking, attention to detail, communication, organization, problem solving, and collaboration skills.

Preferred Qualifications
  • Bachelor's degree candidates with an expected graduation date between December 2027 and June 2028.
  • Coursework, projects, research, student organizations, or internship experience related to data analytics, finance, actuarial science, quantitative modeling, data science, business analysis, architecture, AI, or emerging technologies.
  • Coursework, projects, research, or internship exposure to data requirements, source-to-target mapping, data quality and controls, metadata, lineage, or data governance.
  • Experience using analytical, reporting, or presentation tools such as Excel, PowerPoint, SQL, Python, R, SAS, Tableau, Power BI, or similar platforms.
  • Exposure to financial modeling, dashboard development, statistical analysis, scenario analysis, model documentation, data quality review, metadata, or data lineage concepts.
  • Interest in AI governance, model risk management, responsible AI, explainability, enterprise data architecture, predictive analytics, or quantum computing research.
  • Familiarity with project, portfolio, or workflow tools such as Jira, Rally, Confluence, SharePoint, Microsoft Project, or related platforms.
  • Curiosity about Agentic AI reporting, AI enabled analytics, productivity tools, automated insight generation, and responsible validation of AI generated recommendations.
  • Ability to build clear narratives from data, communicate findings clearly, and work effectively across finance, technology, architecture, risk, product, and business teams.

Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and will contact qualified candidates regarding next steps.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
Ideal Candidate Profile
We are seeking curious and analytical students who enjoy working with data, solving complex problems, and learning how analytics can support responsible technology decisions. Successful candidates will combine quantitative thinking, business curiosity, strong communication skills, and a commitment to accuracy, integrity, and continuous learning.
About Us
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the Team
We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
  • Competitive base salaries
  • Flexible work arrangements and schedules with hybrid and virtual options with Amex Flex
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counselling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit out Colleague Benefits Site.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
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The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

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