GoLang Data Engineer - W2 Contract - No Sponsorship available

Position: GoLang Data Engineer

Location: St. Louis, MO (Remote)

Duration: 1 year of Contract on W2

Required Qualifications:

• 4 years GoLang
• 8 years Development
• building and maintaining data-intensive APIs using a RESTful approach
• Apache Kafka - Stream processing
• Docker - creating containerized application deployments
• Protocol buffers and gRPC
• Unit Testing and Test Driven Development
• Working in AWS, Azure or Google Cloud Platform, Apache Beam or Google Cloud Dataflow, Google Kubernetes Engine or Kubernetes
• data modeling for large scale databases, either relational or NoSQL

Preferred - Not required:

• Experience working with scientific datasets, quantitative science to business problems
• Bioinformatics experience, especially large scale storage and data mining of variant data, variant annotation, and genotype to phenotype correlation

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

Project your talent into relevant projects. Strength of ideas trumps position on an org chart

If you share our values, you should have:

At least 8 years experience in software engineering

At least 4 years experience with Go / GoLang

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

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.