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Qualys

Senior Big Data Engineer

Reposted One Month Ago
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In-Office
Pune, Mahārāshtra
Senior level
In-Office
Pune, Mahārāshtra
Senior level
Lead design, development, and support of a scalable, distributed SaaS security risk platform. Provide technical leadership on data platform, pipelines, and architecture; prototype and implement big data solutions; ensure performance, scalability, security and compliance; mentor engineers; collaborate with product, services and sales; perform benchmarking, troubleshooting, and guide cross-team delivery.
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Description
We are seeking a talented Sr. 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: 
Be the thought leader in data platform and pipeline along with Risk Evaluation. 
Provide technical leadership to the engineering organization on data platform design, roll out and evolution. 
Liason to product teams, professional services and sales engineers on solution and trade-off reviews and represent engineering in such conversations. 
Drive technology explorations and roadmaps. 
Serve as a technical lead on our most demanding, cross-functional departments. 
Ensure the quality of architecture and design of systems. 
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. 
Able to document the details so it will be easy for developers to understand the requirements. 
Assisting developers with proper requirements and directions. 
Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members. 
Exert technical influence over multiple teams, increasing their productivity and effectiveness by sharing your deep knowledge and experience. 
Able to share knowledge and train others. 
Qualifications
Bachelor’s degree in computer science or equivalent 
5+ years of total experience.

Required Skills: Java/Scala, Apache Spark, Kafka, Hadoop, RDBMS (Oracle or equivalent), and NoSQL databases (Cassandra or equivalent).
Experience building scalable, enterprise-grade big data solutions using either Java or Scala. 
2+ 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. 

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