Bioinformatics Analyst Position In San Francisco, CA

Job Description

Key Duties/Responsibilities:

  • Develop and support NGS pipelines using scientific workflow language via best practices, including unit testing, CI/CD, containerization, and code reviews.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
  • Design, develop and maintain Application Programming Interfaces (APIs), microservices, and asynchronous queuing systems.
  • Work with bioinformatic scientists as the stakeholders to assist with data-related technical issues and support their data infrastructure needs.

Education/Experience Requirements:

  • Bachelor or Master in Software Engineering, Computer Science, data Science/engineering, bioinformatics, computer and electrical engineering, or a related field
  • With at least 3-5 + (BS) or 2 + (MS) years of relevant experience.
  • Bioinformatics pipeline development experience

Must Haves:

  • NGS bioinformatics pipeline development experience
    • Understanding the process of how data is developed and processed through the sequencing machine
  • Scientific workflow language experiences such as NetFlow, SnakeMake, CWL or WDL
  • Fluency in 1 or more or relevant programming languages (e.g., Python, Java, R)
  • Experience across multiple tiers of an application, including a database, network, operating system, and containers
  • Familiarity with standard tools and data formats related to genomics resequencing projects processing and analysis.
  • Familiarity with data workflow development and ETL process.
  • Strong communication skills in a collaborative environment

Plusses:

  • AWS Data Platform experience: S3, Kinesis, Dynamo, RDS

Job Requirements

Bioinformatiocs, Snakemake, Netflow, CWL, WDL, Pipeline, workflow

 

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