Lead, Big Data Engineer

Description

We are seeking a talented Lead Big Data Engineer to deliver roadmap features of Unified Asset Inventory. This is a great opportunity to be an integral part of a team building Qualys next generation Micro-Services based platform processing over a 100 million transactions and terabytes of data per day, leverage open-source technologies, and work on challenging and business-impacting projects.

Responsibilities :

You will be building the Unified Asset Management product in the cloud

You will be building highly scalable Micro-services that interacts with Qualys Cloud Platform. Research, evaluate and adopt next generation technologies

Produce high quality software following good architecture and design principles that you and your team will find easy to work with in the future

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.

Qualifications :

• Bachelor’s degree in computer science or equivalent
• 10+ years of total experience.
• 4+ years of relevant experience in design and architecture Big Data solutions using Spark
• 3+ years experience in working with engineering resources for innovation.
• 4+ years experience in understanding Big Data events flow pipeline.
• 3+ years experience in performance testing for large infrastructure.
• 3+ In depth experience in understanding various search solutions solr / elastic.
• 3+ years experience in Kafka
• In depth experience in Data lakes and related ecosystems.
• In depth experience of messing queue
• In depth experience in giving requirements to build a scalable architecture for Big data and Micro-services environments.
• In depth experience in understanding caching components or services
• Knowledge in Presto technology.
• Knowledge in Airflow.
• Hands-on experience in scripting and automation
• In depth 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.
• Design and implement secure big data clusters to meet many compliances and regulatory requirements.
• Experience in leading the delivery of large-scale systems focused on managing the infrastructure layer of the technology stack.
• Strong experience in doing performance benchmarking testing for Big data technologies.
• Strong troubleshooting skills.
• Experience leading development life cycle process and best practices
• Experience in Big Data services administration would be added value.
• Experience with Agile Management (SCRUM, RUP, XP), OO Modeling, working on internet, UNIX, Middleware, and database related projects.
• Experience mentoring / training the engineering community on complex technical issue.