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Scientific Data Engineer – Data Analytics and Curation

Department: 4000 - Data and Technology
Location: Seattle

Scientific Data Engineer – Data Analytics and Curation

We are looking for an experienced Scientific Data Engineer (data scientist) who has a track record of creating data processing and ETL modules for large scale datasets. This position will work closely with research and data production teams to support data ingest, curation and integration of large scale and diverse data on an ongoing basis.

The ideal candidate will have a strong background in data analytics, as well as software engineering and DevOps skills. You will interact regularly with neuroscientists and a wide variety of engineers both internally and as part of a large consortium, collaborating on developing a vast resource on the brain.      

To gain more insight on the projects you will impact, please visit the Allen Brain Map data portal (portal.brain-map.org) and BICCN portal (biccn.org)

Essential Duties and Responsibilities:

  • Contribute to onboarding of consortium data managers to ensure data quality.
  • Design/prototype integration of external data sources and annotations into product.
  • Develop and maintain scripts for automatic updates from external ontologies and databases, and ETL to ingest format.
  • Codevelop requirements for ingest of feature integration and collaborate with compute pipelines for integration; prototype integration of derived data features into the data model for search, analysis and inferencing.
  • Develop documentation for data workflows, software and processes.
  • Support integration of spatial features derived from mapping of data to common coordinate frameworks.
  • Possible inference and search prototype to validate ontologies.
  • Monitor ongoing data quality and analysis results, working with data generation teams to process and analyze the data.
  • Co-develop requirements for tools to support data ingest, ETL and dashboarding.
  • Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, providing feedback for re-designing infrastructure for greater scalability.
  • Support infrastructure for optimal extraction, transformation, and loading of data from a wide variety of data sources.
  • Perform basic quality control of data including tests for data integrity after ETL; test usability of the data during product prototyping
  • Collaborate effectively with experts in diverse scientific and engineering topics, including neuroscience, high performance scientific computing, computer vision, and web applications
  • Apply a modern software engineering workflow, including emphasis on code review, continuous integration, and automatic testing.

Required Qualifications:

  • Bachelor’s degree.
  • Minimum of 3 years of relevant experience.
  • Experience building and optimizing ETL workflows.
  • Strong project management, communication and organizational skills.
  • Experience with command line development tools in a Linux environment.
  • Extensive experience in scientific computing software in Python and/or Scala.
  • Advanced working SQL knowledge and experience working with relational and graph databases.
  • Demonstrated experience in data analysis, preferably in signal processing and numerical methods.
  • Familiarity with entire software toolchain, including source code management (git), debuggers, build tools, and testing methodologies.
  • Experience writing code and configuring systems to facilitate automated testing, building, and deployment of software.
  • Ability to gather requirements from collaborators, synthesize into development work items, describe to colleagues and discuss implementation ideas, record issues, execute and complete.

Preferred Qualifications:

  • Experience with biological datasets.
  • Experience writing code for continuous delivery.
  • Advanced degree in a relevant technical discipline.
  • History of contributing to open source and/or team-based projects.

Work Environment:

  • Sitting, standing, bending, squatting as found in typical office environment.
  • Occasional exposure to laboratory atmosphere - possible exposure to chemical, biological or other hazardous substances.

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.

 

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