Big Data Engineer
1 week ago
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.
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