Data and Analytics Engineer
Confirmed live in the last 24 hours
Cloudflare
Job Description
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.
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!
Available Locations: Lisbon, Portugal
About the team
You will be part of the Radar team within Cloudflare’s ETI Engineering department. Emerging Technologies & Incubation (ETI) is where new and bold products are built and released within Cloudflare. Rather than being constrained by the structures which make Cloudflare a massively successful business, we are able to leverage them to deliver entirely new tools and products to our customers. Cloudflare’s edge and network make it possible to solve problems at massive scale and efficiency which would be impossible for almost any other organization.
About the role
We are looking for an experienced Data and Analytics Engineer to join our team to scale our data insights initiatives. You will work with a wide array of data sources about network traffic, performance, and reliability. You’ll be responsible for building data pipelines, doing ad-hoc analytics based on the data, and automating our analysis. Important projects include understanding Internet trends and insights based on data produced by Cloudflare’s broad product portfolio.
A candidate will be successful in this role if they’re flexible and able to match the right solution to the right problem and work at multiple levels of the stack. Flexibility is key. Cloudflare is a fast-paced environment and requirements change frequently.
What you'll do
- Work closely with other product and engineering teams to ensure our products and services collect the right data for our analytics;
- Extract, clean, and analyze complex datasets from various sources;
- Design,implement and maintain data pipelines (ETL's) that take unprocessed data and make it usable for advanced analytics;
- Develop and automate reports and iteratively build and prototype dashboards to provide insights at scale;
- Build tooling, automation, and visualizations around our analytics for consumption by other Cloudflare teams.
Examples of desirable skills, knowledge and experience
- Strong Python and SQL skills;
- Experience with Linux container environments (Docker, Kubernetes);
- Understanding of modern software development lifecycles, including CI/CD;
- High-level understanding of networking and most common Internet protocols;
- Solid understanding of computer science fundamentals including data structures, algorithms, and object-oriented or functional design (e.g. B.S. or M.S. in Computer Science, Engineering, Mathematics, or related fields);
- Minimum 3 years of industry experience in software engineering, data engineering, data analysis, or related field;
- Excellent data analysis skills, with a natural curiosity to query and manipulate data to answer challenging questions;
- Strong communication and collaboration skills, with a proven ability to partner with cross-functional teams, navigate ambiguous business requirements, and articulate complex data insights to both technical and non-technical audiences w
