Simply put; Skimlinks is an ambitious technology and product startup, building cool stuff, at scale. We build highly transactional, high throughput platforms that connect publishers, merchants, and audiences; which allows some of the most popular sites in the world to efficiently and easily monetise their curated journalistic content. We partner with companies like Huffington Post, The New York Times, The Independent and Hearst to diversify their content monetisation strategies; which helps them create more of the journalistic content that we all consume and enjoy, without relying upon additional banner advertising. We’re also using our massive amount of anonymous behavioural data to create greenfield data platforms. We employ a diverse array of advanced Machine Learning and Classical Statistical methodologies to interrogate our dizzying amounts of data. Though our platforms, we have a direct view of the browsing and shopping behaviors of over 650 million users; amassing over 1TB of data daily across over a billion incoming events. As Staff Software Engineer, you’ll work closely with the CTO to provide inspirational technical and architectural leadership and mentoring across the company, and you’ll own some of the most strategic and challenging efforts from concept through implementation and evolution. For those with both desire and aptitude, this role could include both team as well as technical management. Whether you’ve built APIs; or systems that scale to billions of requests daily; or worked with terabytes of incoming data; or integrated with complex partner ecosystems; we have a lot of different problem spaces that you will enjoy. Our primary language is Python, but we look for amazing engineers and computer scientists (not just programmers), so we welcome and expect people to have a range of backgrounds – we particularly favour intellectually curious, polyglot engineers who have built platforms of high scale and high complexity and who love to solve hard problems. Responsibilities: You will design, build, implement, and own systems across all parts of our platform; from high-volume data collection, enrichment and automated analysis, through to backend services and RESTful APIs You should keep on top of the latest and greatest developments in distributed systems; the cloud; and data science fields. You will motivate and inspire the team to deliver the Skimlinks technical vision You will lead by example; in order to foster a culture of Engineering excellence and craftsmanship Contribute to overall technical strategy and lead the teams on architectural design and decision making Mentor and guide team members to deliver better software, faster Lead on technology product, practice and tool selection Obsess over non-functional requirements such as performance, security, testability, maintainability and reliability Contribute to the product roadmap and ensure the technical and product visions are aligned Help define our development environment, and communicate the best development practices within the organisation (i.e. code reviews, testing, etc). Sharing your knowledge across (and possibly outside) the company in your areas of expertise Requirements: You should possess a Degree in Computer Science or Software Engineering (or equivalent) You have deep experience building enterprise-grade software with several languages, such as Java, C#, F#, Scala, C++ or Python You have been an Architect or Lead Software Engineer previously in your career, in brilliant software development teams working in technically challenging environments You are familiar with building systems that efficiently scale with very large data volumes You’re obsessed with how your applications will hold up in production, with real users doing bad things to them You’ve led and mentored teams, such as in the use of design and integration patterns, domain modelling and engineering excellence. You have (or are at least receptive to) running and participating in industry events A flavour of our Technology Stack: Python Java Spark Hadoop Hive Google Cloud Platform AWS S3 Tensorflow