JOB DUTIES: Develop, create, and modify DNA analysis software and specialized utility programs. Analyze user needs and develop solutions for genealogy software applications. Design software and customize software for client use with the aim of optimizing operational efficiency. Modify existing software to correct errors and improve its performance. Create web pages using node.js, React, and JSON APIs. Create back-end services using Java, Maven, and SpringBoot. Practice good coding techniques including writing unit tests, doing commits and pull requests, etc. Collaborate with other engineers to develop scalable, resilient, and maintainable web pages and to find the best solution. Participate in an on-call rotation to ensure the availability of the website. Manage the AWS cloud infrastructure needed for our pages using company-provided tools. This includes allocating the right CPU, memory, and auto-scaling policies in a way that provides a good customer experience while minimizing costs. Collaborate with product managers and UX designers to communicate feasibility of ideas, set reasonable expectations of time for completion, and find ways to accomplish these goals with fellow engineers.

POSITION REQUIREMENTS: Master's degree in Computer Science or related discipline, or foreign equivalent, and two (2) years of experience in the job offered or in a closely related position.

WORKSITE: 1300 West Traverse Parkway, Lehi, Utah, 84043, United States. Telecommuting accepted from anywhere within the United States.   SPECIAL REQUIREMENTS: 

Experience must include one (1) year of professional experience with Java.

Additionally, the following skills must have been gained through education, training or experience as specified:

•            Programming languages such as C, C#, Java, or Python •            Database expertise with one more of the following: Relational DB (SqlServer, MySql, etc), Hadoop or Sparc •            Data crawling/analysis •            Back-end data gathering for data visualization •            Machine learning and information retrieval

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