Big Data Engineer

We are seeking a talented Big Data Engineer to deliver roadmap features of Enterprise TruRisk Platform which would help customers to Measure, Communicate and Eliminate Cyber Risks. Working with a team of engineers and architects, you will be responsible for prototyping, designing, developing and supporting a highly scalable, distributed SaaS based Security Risk Prioritization product. This is a fantastic opportunity to be an integral part of a team building Qualys next generation platform using Big Data & Micro-Services based technology to process over billions of transactions data per day, leverage open-source technologies, and work on challenging and business-impacting initiatives. Responsibilities: Liason to product teams, professional services and sales engineers on solution and trade-off reviews and represent engineering in such conversations. Support the team in technology explorations and roadmaps. Functionally decompose complex problems into simple, straight-forward solutions. Fully and completely understand system interdependencies and limitations. Possess expert knowledge in performance, scalability, enterprise system architecture, and engineering best practices. Leverage knowledge of internal and industry prior art in design decisions. Effectively research and benchmark cloud technology against other competing systems in the industry. Qualifications: Bachelor's degree in computer science or equivalent 2+ years of total experience. 2+ years of relevant experience in design and architecture Big Data solutions using Spark 2+ years experience in working with engineering resources for innovation. 2+ years experience in understanding Big Data events flow pipeline. 2+ years experience in performance testing for large infrastructure. Understanding various search solutions solr/elastic. Understanding in Kafka Knowledge in Presto technology. Knowledge in Airflow. Hands-on experience in scripting and automation Understanding of RDBMS/NoSQL, Oracle , Cassandra , Kafka , Redis, Hadoop, lambda architecture, kappa , kappa ++ architectures with flink data streaming and rule engines Experience in working with ML models engineering and related deployment. PRB