Big Data Engineer
HUB International Limited ("HUB") is the 7th largest global insurance and employee benefits broker, providing a broad array of property, casualty, risk management, life and health, employee benefits, investment and wealth management products and services. With over 10,000 employees in 450 offices throughout North America, HUB has grown substantially, in part due to our industry leading success in Mergers and Acquisitions. The company is headquartered in Chicago and is currently owned by Hellman & Friedman.
About the Position:
The Big Data Engineer will lead the development of applications or system software and improve the efficiency of information processing systems. The candidate should have experience in designing, developing and testing a company's data management software, ensuring that it meets business requirements and industry practices. This position requires experience in training internal and external resources to integrate new products and software packages into the system in the organization.
- Responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale data mining solutions
- Designs and implements data-oriented applications using a wide variety of technologies, including Microsoft's Cloud technology stack (Azure).
- Implement data-intensive, horizontally-scalable systems (such as on Map-Reduce frameworks like Hadoop, Spark, etc.).
- Develops distributed applications to solve large scale processing problems, utilizing various languages like Java, Scala , Shell etc.
- Implements, troubleshoots, and optimizes solutions based on modern big data technologies like Hadoop, Spark, Elastic Search, Storm, Kafka, etc. in both an on premise and cloud deployment model
- Implements data architecture, including data ingress in batch and real time from a broad variety of external systems; data transformations to prepare data for analytics processing, and data egress for availability of analytics results to visualization systems, applications, or external data stores
- Supports documentation, change control, and QA processes consistent with enterprise requirements
- Establishes strong teamwork with client technical resources, and effectively communicates project status, technical issue options and resolution, and operational requirements to client stakeholders
- Communicate via RESTful APIs with HTTP and JSON
- Research and development of novel technologies and methodologies for extreme scale data analytics, big data processing, data mining, and machine learning on traditional and emerging computing architectures
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems or related field preferred
- 7 to 10 years of experience in a professional capacity as described above
- Experience with one or more of the cloud products: Azure, Amazon AWS, OpenStack, CloudFoundry, Mesos and Docker
- Very strong server-side Java or .NET experience, especially in an open source, data-intensive, distributed environments
- Expert in the Hadoop Framework & java programming (i.e. Spark, MapReduce, Pig, Hive, Kafka, Storm, etc.) including performance tuning
- Good understanding of algorithms, data structure, and performance optimization techniques
- Experience with agile development methodologies like Scrum
- Self motivated, and has the ability to drive technical discussions
- Organized, detail oriented, able to work both independently and in a team
- Excellent problem solver, analytical thinker and quick learner
- Strong verbal and written communication skills
- Proficient in Data Architecture, Master Data Management and Governance
- Experience in NoSQL DB such as Cassandra and MongoDB
- Certifications a plus: Amazon, Cloudera, Spark
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