Data Engineer Intern (Summer 2026)
CloudflareIn-OfficePosted 24 February 2026
Job Description
<div class="content-intro"><div><strong>About Us</strong></div>
<div>
<p>At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. </p>
<p><span style="font-weight: 400;">We realize people do not fit into neat boxes. We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills, and we are ready to help you do that. We cannot complete our mission without building a diverse and inclusive team. We hire the best people based on an evaluation of their potential and support them throughout their time at Cloudflare. Come join us! </span></p>
</div></div><p><strong>Available location(s): Austin, US</strong></p>
<h4><strong>About the team</strong></h4>
<p>The Data Intelligence Analytics team at Cloudflare is responsible for building a centralized analytics platform and cloud data lake that enables our internal Business Partners and Product teams with actionable insights and also provides a 360 view of our business. Our goal is to democratize data, support Cloudflare’s critical business needs, provide reporting and analytics via self-service tools to fuel existing and new business critical initiatives.</p>
<p><strong>About the role</strong></p>
<p>This internship is targeting students with experience and interest in Data Engineering.</p>
<p>The Data Engineer Intern delivers full-stack data solutions across the entire data processing pipeline. This role relies on systems engineering principles to design and implement solutions that span the data lifecycle - collect, ingest, process, store, persist, access, and deliver data at scale and at speed. It includes knowledge of local, distributed, and cloud-based technologies, data virtualization, and all security and authentication mechanisms required to protect the data. </p>
<h4><strong>What you'll do</strong></h4>
<ul>
<li>Work through all stages of a data solution lifecycle – analyze / profile data, create conceptual, logical and physical data model designs, architect and design ETL, reporting and analytics</li>
<li>Knowledge of modern enterprise data architectures, design patterns, and data tool sets and the ability to apply them</li>
<li>Identify key metrics and build exec-facing dashboards to track progress of the business and its highest priority initiatives</li>
<li>Identify key business levers, establish cause effect, perform analysis, and communicate key findings to various stakeholders to facilitate data driven decision-making</li>
<li>Work closely across the business teams like Finance, Sales, Marketing, Legal, Customer Support, Product, Engineering</li>
</ul>
<p><strong>Examples of desirable skills, knowledge, and experience</strong></p>
<ul>
<li>Currently enrolled in M.S in Computer Science, Engineering or related STEM field </li>
<li>Experience working with Go, Python, SQL, Java, or equivalent programming languages</li>
<li>Experience working with distributed systems (Spark etc.)</li>
<li>Hands-on experience in data pipelines/ frameworks development</li>
<li>Ability and interest to learn new skills and technologies quickly</li>
<li>Excellent communication and problem-solving skills</li>
<li>Ability to commit to a 12 week summer internship</li>
<li>In office 3-4 days a week in Austi ... (truncated, view full listing at source)
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