Why Carbon Black?
At Carbon Black, you’ll have the opportunity to make a huge impact while working alongside a global community of passionate people who are leading the way in cutting-edge technology. Our valued employees across the world have made Carbon Black a Top Place to Work, as named by the Boston Globe for two consecutive years.
Our Engineering team is moving at lightning speed on the breaking edge of technology. You’ll be pulling things apart and tinkering, building new platforms, or playing in the cloud. Here, the engineering opportunities are endless. With this fast-paced, synergetic group, you’ll be working together and across the organization to ensure customer success all while continuing to build a product that protects their dearest assets.
Why You Matter:
There’s incredible excitement and urgency around cyber security software right now. Protecting the world’s Intellectual Property is an imperative and Carbon Black is at the forefront of this market, providing solutions that protect industry and thought leaders in the Commercial, Retail, Finance, Energy and Government sectors.
We’re looking for a Big Data Architect to take ownership of the overall information architecture that will enable our Data Science and Threat Research teams to efficiently access the data that they need to do their jobs. You will understand everything from data warehousing, to modern NoSQL data stores and analytics technologies and also be a big-picture architect, able to design schemas and build an information architecture that consists of extracting or streaming data from source systems, all while maintaining data quality. You will have experience both in designing ETL for batch processing as well as data streaming architectures and have a strong background in analytics.
What You’ll Do:
Primary: Architecting storage of terabytes of raw and processed data for analysis
Primary: Designing ETL from existing internal data sources
Primary: Designing streaming data architectures
Primary: Designing systems for cleaning, normalizing, and sampling data for use in machine learning algorithms
Primary: Designing data schemas tuned for ad-hoc and scheduled analytics
Secondary: Statistical analysis of data
