Data Architect
Confirmed live in the last 24 hours
Tempus

1,001-5,000 employees

AI-driven precision medicine through clinical and molecular data analysis
Company Overview
Tempus Labs, Inc. is a leader in precision medicine, leveraging artificial intelligence to analyze vast clinical and molecular data, enabling physicians to deliver personalized, data-driven care. The company's advanced machine learning platform and unique solution sets facilitate the discovery, development, and delivery of optimized therapeutic options for patients. With a focus on extensive molecular profiling, Tempus has developed a robust pan-cancer tumor organoid platform and validated a liquid biopsy assay, demonstrating their commitment to transforming personalized patient care and their position at the forefront of the healthcare industry.
AI & Machine Learning
Data & Analytics

Company Stage

N/A

Total Funding

$1.4B

Founded

2015

Headquarters

Chicago, Illinois

Growth & Insights
Headcount

6 month growth

12%

1 year growth

28%

2 year growth

49%
Locations
Chicago, IL, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Google Cloud Platform
SQL
Python
NoSQL
CategoriesNew
Data & Analytics
Software Engineering
Requirements
  • You have domain knowledge in healthcare and next generation sequencing data
  • You have strong experience and knowledge of 3NF, dimensional (star schema), and data vault modeling techniques
  • You have applied exceptional SQL skills in an enterprise data warehouse environment
  • You have knowledge of ETL/ELT and BI architectures, concepts and frameworks
  • You understand and can clearly articulate the long-term impacts of key decisions between database technologies (relational, MPP, NoSQL) and have experience architecting solutions across multiple technologies
  • You have experience with data modeling tools like Erwin, Vertabelo or Lucidchart
Responsibilities
  • Manage an enterprise data model in collaboration with engineers, product managers, scientists, and operators to integrate structured data from source systems in multiple complex domains (clinical records, genomics, NGS lab, radiology, et al.)
  • Author and maintain entity-relationship diagrams, data dictionaries, API specs, and data translation documentation at multiple levels of abstraction (conceptual, logical, physical) and across multiple data store technologies (relational, NoSQL)
  • Advocate and educate engineering team members on data modeling rules, standards, and best practices
  • Evaluate completeness of source system data models and data by profiling partner data
  • Implement solutions to proactively monitor data quality with traceability to source systems
Desired Qualifications
  • Experience with GCP architecture
  • Experience working with clinical and/or genomic data
  • Experience writing and debugging Python
  • Implementing master, reference, or metadata management solutions