Senior Engineer, Genomics Data

Lake County, IL, US
Aug 09, 2019
Science/R&D, Genomics
Required Education
Bachelors Degree
Position Type
Full time
The Genomics Research Center (GRC) is a center of excellence for genetics and genomics that supports both Discovery and Development. The GRC plays an integral role towards our goal of developing world class genetics and genomics research, focusing on finding the right targets and helping us better understand not only human disease biology but also the behavior of and response to our drugs in clinical trials. Within the GRC, the Department of Bioinformatics is responsible for data analysis and provides analytical insight for both internal and external data. This involves the identification and characterization of underlying genetic, epigenetic, or genomic factors that are associated with disease diagnosis, prognosis and response (efficacy and safety) to drug treatment, identification of new targets, and interpretation of the impact of genetic and genomic evidence from population-based studies. We have an exciting opportunity for a Senior Engineer, Bioinformatics, based in Lake County, IL.

Key Responsibilities:

  • Optimize existing pipelines, workflows, and systems, as well as engineer new pipelines, workflows, and systems
  • Translate and implement algorithms and protocols in a high performance computing environment
  • Develop and maintain data repositories in a structured manner for semi-automated computational reassessment and record keeping
  • Develop and manage new and existing RShiny visualization tools

Level and compensation will be commensurate with experience.


  • BS, MS (preferred), or Ph.D in Computer Science, Bioinformatics, Software Engineering, Computer and Electrical Engineering, or related field, with at least 10+ (BS), 8+ (MS), 0+ (Ph.D) years of relevant experience
  • A high degree of technical competency and strong communication ability, as well as fluency in 2 or more or relevant programming languages, such as R, Python, Perl, Java, or C++; Data visualization methods like D3, R Shiny, or Spotfire; Database management tools including SQL, SQLite, or MongoDB
  • Demonstrated expertise in Linux environments, distributed computing, and HPC in local and cloud computing environments.
  • Candidates should be familiar with standard tools and data formats related to gene expression, enrichment analysis, genetic, genomic, or epigenetic data (e.g, that which is encountered when analyzing high-throughput transcriptomic, whole exome, whole genome, whole methylome, GWAS, or targeted resequencing data).
  • Strong communication skills in a collaborative environment.


  • Individuals with experienced interpreting biological data related to diseases associated with cancer, neurodegenerative disease, immunological, or metabolic disorders are also desired
Additional desired skills include:
  • Experience analyzing and interpreting gene expression data for understanding disease mechanisms and model organism prioritization
  • Fluency with consortium disease specific (like the Accelerating Medicines Partnership - Alzheimer's Disease, the Cancer Genome Atlas) or genomic databases (such as those relating to genome annotation, genetic variants, public data repositories).