This is a fully Remote and Work From Home (WFH) opportunity within the US

Science 37 is accelerating the research and development of breakthrough biomedical treatments by bringing clinical trials to patients' homes. Backed by venture investors such as Glynn Capital, Google Ventures, Redmile Group, dRx Capital and Lux Capital, we are revolutionizing the clinical trial industry, one patient, at a time. To help us achieve our goal, we are seeking a Data Engineer eager to make an impact within a mission-driven organization.

Job Responsibilities 

  1. Collaborate with engineers, product managers and business SME’s to understand data needs 
  2. Design, build and maintain reliable data pipelines to move data across multiple platforms including Data Lake, Data Warehouse and various application platforms 
  3. Ingests data from a variety of internal and third-party sources 
  4. Connects to data sources using API’s, data pipelines and files 
  5. Defines and implements a robust automated data pipeline using modern techniques 6. Design, implement, and support data warehouse / data lake infrastructure using Python, Redshift and other AWS services 
  6. Aligns architecture with business requirements incorporating design for security and performance optimization 
  7. Ensures and improves data reliability, linage, efficiency, and quality 
  8. Develops data set processes and best practices 
  9. Build data expertise and own data quality 
  10. Provides accurate project effort estimates 


  1. 5+ years of experience as a Data Engineer or in a similar role 
  2. 4+ years of experience in Python or any other object oriented language 
  3. 3+ years of experience working with AWS tech stack, Redshift, S3, EC2, Lambda etc.
  4. 3+ years of ETL Management/Data Pipeline experience 
  5. 2+ years of Data Architecture and Design experience 
  6. Strong understanding of ETL/ELT tools and processes 
  7. Strong experience in SQL 
  8. Proficient in data warehouse solutions, modeling techniques, and performance optimization 
  9. Experience building processes supporting data transformation, data structures, metadata, dependency, and workload management 
  10. Demonstrated analytical, technical, and problem-solving skills 
  11. Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations 


  1. Strong interpersonal skills, and the ability to communicate and manage well at all levels of the organization 
  2. Action oriented and innovative; able to translate goals into achievable steps 3. Strong collaborative team player 
  3. Ability to effectively handle multiple tasks and ability to adapt to changes in workload and priorities 
  4. Excellent planning, prioritization, and organizational skills
  5. High level of integrity and dependability with a strong sense of urgency and results-orientation 
  6. Detail-oriented, and organized with strong verbal and written communication skills 8. Bachelor of Science Degree or equivalent experience in the Life Sciences field


  1. Ability to communicate in English (both verbal and written)

Science 37 values the well-being of its employees and aims to provide team members with everything they need to succeed.

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