[Remote] IT Cloud Engineer
Note: The job is a remote job and is open to candidates in USA. TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan, offering strategic talent solutions to clients worldwide. They are seeking an IT Cloud Engineer to be a critical senior member of a data engineering team focused on creating distributed analysis capabilities around large datasets, while applying software craftsmanship and innovative solutions.
Responsibilities
- Be a critical senior member of a data engineering team focused on creating distributed analysis capabilities around a large variety of datasets
- Take pride in software craftsmanship, apply a deep knowledge of algorithms and data structures to continuously improve and innovate
- Work with other top-level talent solving a wide range of complex and unique challenges that have real world impact
- Explore relevant technology stacks to find the best fit for each dataset
- Pursue opportunities to present our work at relevant technical conferences
- Project your talent into relevant projects. Strength of ideas trumps position on an org chart
Skills
- At least 7 years experience in software engineering
- At least 2 years experience with Go
- Proven experience (2 years) building and maintaining data-intensive APIs using a RESTful approach
- Experience with stream processing using Apache Kafka
- A level of comfort with Unit Testing and Test Driven Development methodologies
- Familiarity with creating and maintaining containerized application deployments with a platform like Docker
- A proven ability to build and maintain cloud based infrastructure on a major cloud provider like AWS, Azure or Google Cloud Platform
- Experience data modeling for large scale databases, either relational or NoSQL
- Experience with protocol buffers and gRPC
- Experience with: Google Cloud Platform, Apache Beam and or Google Cloud Dataflow, Google Kubernetes Engine or Kubernetes
- Experience working with scientific datasets, or a background in the application of quantitative science to business problems
- Bioinformatics experience, especially large scale storage and data mining of variant data, variant annotation, and genotype to phenotype correlation
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