Software Engineer - Early Career

Datadog
Lisbon, PortugalPosted 6 April 2026

Job Description

We’re looking for early-career engineers to help us collect, aggregate, visualize, and analyze high-scale metrics, logs, and application data. Software engineering at Datadog includes a variety of exciting opportunities. Interested in distributed systems or Kubernetes across tens of thousands of nodes? Looking to build out products like Real User Monitoring or Cloud Security Management or perhaps join one of our internal teams helping engineering teams ship apps quickly? Want to see your work actually impact and improve the product in a meaningful way? We’ve got you covered. Whether you’re writing a new integration, building data pipelines, or working with the open-source community, our early-career engineers are key contributors to our product. Datadog offers the unique opportunity to work on large-scale, real-time systems by engineers for engineers. Our product is multi-cloud and collects more than a hundred trillion events per day for 28,000+ customers. Early-career engineers work towards the same objectives as their senior teammates to bring lasting impact to our products. We place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. Our hybrid workplace ensures our employees can create a work-life harmony that best fits them. Students can sign up anytime for a free Datadog Pro account ! What You’ll Do: Solve a scaling bottleneck in a critical service Deploy a new feature to production and progressively roll it out with feature flags Investigate and fix a production issue from a service your team owns Create a way to optimize a service to handle more traffic at scale In partnership with your team, plan the most important projects to work on next Who You Are: You are in the process of receiving/have a degree in Computer Science, Software Engineering or related scientific field, or equivalent experience You are targeting a 2026 full-time start date You are comfortable coding in one or more languages You value code simplicity and performance You want to work in a fast-paced environment that values its employees and customers You are a self-starter who enjoys partnering with other engineers and solving difficult problems You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You’re looking for or have some exposure using AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output Bonus: you’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: New hire stock equity (RSUs) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing Intradepartmental mentor and buddy program for in-house networking An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups) and monthly company social events Unlimited snacks and drinks in our office; catered lunches on Monday, Wednesday, and Friday Free, global mental health benefits for employees and dependents age 6+ Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. Please ensure that you submit your CV/resume in English. If possible, please apply using your personal email address instead of your university email address. #LI-Onsite About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud ... (truncated, view full listing at source)
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