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Sr. Science Research Specialist (Data Engineer) MINERVA

Description

The Sr. Science Research Specialist (Data Engineer) will be responsible for expanding and optimizing MINERVA Project and ACCeSs@AIM’s data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. S/he is a data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. S/he will support our data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing and designing data pipelines for high-impact academic, government and industry projects.

  • Qualifications
  • Responsibilities

Education

  • Undergraduate or Graduate degree in Computer Science, Physics, Statistics, Informatics, Information Systems or other related field.

Minimum experience

  • At least 2 years of experience in transforming underlying data into functional data sets in order to generate meaningful insights, working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Business Understanding

  • Strong analytic skills related to working with unstructured datasets, working Python knowledge, familiar with C++, R, and/or Python, and experience building and optimizing data pipelines, architectures, and data sets.
  • Ensure proper handling of datasets (both existing and yet-to-be-collected) related to the project.
  • Spearhead the creation of the automated pipelines for data ingestion, harmonization and preprocessing.
  • Create and maintain optimal data pipeline architecture.
  • Assemble large, complex data sets that meet functional / non-functional project requirements.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Bash and Python scripts, and other technologies, both on-premises and on the cloud.
  • Support the team members in creating a robust modelling pipeline for efficient model deployment.
  • Build analytics tools e.g., dashboards, API endpoints and CLI programs, that utilize the data pipeline to provide actionable insights for data scientists and other end-users
  • Work with stakeholders including data scientists and third-party clients to assist with data-related technical issues and support their data infrastructure needs.
  • Teach/assist/mentor students in AIM, as requested; and,
  • Perform ad hoc tasks relevant to the position as needed.

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