Data Engineer
Confirmed live in the last 24 hours
Shape Therapeutics

51-200 employees

Pioneering programmable RNA medicines using AI
Company Overview
Shape Therapeutics Inc. (ShapeTX) is a pioneer in the field of programmable RNA medicines, leveraging a robust AI-driven platform to analyze vast datasets and design effective treatments for a wide range of diseases, from rare genetic disorders to debilitating conditions like Alzheimer's and Parkinson's. The company's unique approach utilizes ADAR, a naturally occurring enzyme, to correct protein-making instructions by recoding RNA, offering a potential solution to numerous genetic disorders without permanently altering DNA. Additionally, ShapeTX's TruStable™ stable cell lines significantly enhance the manufacturability of RNA medicines at any scale, ensuring accessibility for patients.
AI & Machine Learning
Data & Analytics

Company Stage

Series B

Total Funding

$147.5M

Founded

2018

Headquarters

Seattle, Washington

Growth & Insights
Headcount

6 month growth

9%

1 year growth

20%

2 year growth

39%
Locations
Seattle, WA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Redshift
Python
MySQL
Data Science
SQL
Postgres
AWS
Snowflake
CategoriesNew
Data & Analytics
Requirements
  • Bachelor's degree (or equivalent experience) in Information Systems, Computer Science, Computer Engineering, Data Science, or similar technical or engineering experience in a relevant field or discipline. Advanced degrees are a plus
  • Minimum of 3+ years of professional experience as a Data Engineer or in a related role
  • Experience with scientific datasets in the life sciences, pharma, or biotechnology industry
  • Proven experience with database technologies such as SQL (e.g., PostgreSQL, MySQL)
  • Proficiency with scripting languages such as Python
  • Familiarity with the following platforms/tools/ standards is preferred:
  • Data warehousing (e.g., Snowflake, Databricks, or Redshift)
  • Cloud infrastructure, AWS and SaaS, Benchling
  • Modern data engineering and orchestration tools
  • Scientific data standards and formats (e.g., ADF, UDM, etc.)
  • Data visualization tools and techniques
Responsibilities
  • Architect, design, implement and maintain scalable data tools and pipelines to ingest, process, and transform scientific datasets from various sources into standardized and usable formats
  • Enhance performance and reliability of data storage, data pipelines, and data retrieval mechanisms
  • Provide thought leadership on data modeling and metadata management to ensure our data assets are FAIR
  • Implement methods to ensure the accuracy, consistency, and integrity of scientific datasets. Address data quality issues that arise
  • Define the data engineering product strategy and align features and services to experimentalist and data/ML scientists' requirements
  • Maintain detailed technical product documentation for pipelines, models, and processes to ensure reproducibility and knowledge sharing
  • Work with IT security to ensure data solutions comply with security standards and regulations. Implement appropriate security measures to protect data from unauthorized access or breaches