Engineering at BitSight is about results. Our primary focus is on shipping products and features that further the company’s mission of assessing organizations’ security posture by providing objective, verifiable and actionable security ratings. In service of that overarching goal, we employ leading edge technology, organize as dynamic project-based teams, and work in a highly collaborative environment. We move fast, with multiple releases to production daily, yet still ship high quality, robust software.
Our data pipeline team develops and maintains our Big Data code and infrastructure. We process tens of billions of security events per day on AWS clusters with hundreds of cores. We use technologies such as Spark, Hadoop, HBase, and Elasticsearch, and we code in Java, Scala, and Python. We are constantly tackling challenging and fascinating problems in distributed computing, scalability, and reliability as we continue to grow our data volume and extract even more insight from it.
Our backend services team works closely with both our front end developers and data pipeline engineers. Our services process and transform the billions of security events we ingest every day, into a product useable for both our web client and customer APIs, utilizing Django, Scala, and various flavors of Java.
Our Infrastructure Engineering team embeds with development teams to ensure reliable and consistent delivery of services into production. We’re strong believers in infrastructure-as-code. The team is always looking for ways to accelerate and streamline processes, leveraging the latest technologies like Docker and Kubernetes to do just that.
Our data science team strives to keep BitSight Security Ratings the best in the business, enable new features and products, provide thought leadership in the cybersecurity industry, and improve other BitSight business functions by infusing them with data science techniques. We assist in evaluating third party data sources, and work closely with data pipeline engineers to efficiently handle the billions of security events we process daily from hundreds of data sources. We use bleeding edge modeling and machine learning techniques to better understand cyber risk.
Our Cybersecurity Research team tracks cybersecurity developments and works on understanding malware behavior, system vulnerabilities, the effectiveness of network security devices, etc. The team is a trusted member of the cybersecurity community and participates in industry and government activities.