This is a Go Lang Software Developer role who should have 2-3 years of GO Lang exp
Client collects terabytes of data across all aspects of its operations, from genome sequencing, crop field trials, manufacturing, supply chain, financial transactions and everything in between. There is an enormous need and potential here to do something that has never been done before. We need great people to help transform these complex scientific datasets into innovative software that is deployed across the pipeline, accelerating the pace and quality of all crop system development decisions to unbelievable levels.
What you will do is why you should join us:
• 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
If you share our values, you should have:
• 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
Bonus points for:
• 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