Data Platform Engineer
Posted on 2/22/2022
INACTIVE
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

Series G

Total Funding

$1.3B

Founded

2015

Headquarters

Chicago, Illinois

Growth & Insights
Headcount

6 month growth

6%

1 year growth

26%

2 year growth

49%
Locations
Chicago, IL, USA • Dorchester, Boston, MA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Agile
Python
SQL
Docker
REST APIs
Development Operations (DevOps)
Data Analysis
Google Cloud Platform
CategoriesNew
DevOps & Infrastructure
Software Engineering
Requirements
  • You know what it takes to build and run resilient data pipelines in production and have experience implementing ETL/ELT to load a multi-terabyte enterprise data warehouse
  • You have implemented analytics applications using multiple database technologies, such as relational, multidimensional (OLAP), key-value, document, or graph
  • You value the importance of defining data contracts, and have experience writing specifications including REST APIs
  • You write code to transform data between data models and formats, preferably in Python or PySpark
  • You've worked in agile environments and are comfortable iterating quickly
Desired Qualifications
  • Experience moving trained machine learning models into production data pipelines
  • Healthcare domain knowledge and experience with healthcare transmission formats (e.g. FHIR, HL7, ANSI X12) and data models (e.g OMOP)
  • Expert knowledge of relational database modeling concepts, SQL skills, proficiency in query performance tuning, and desire to share knowledge with others
  • Experience building cloud-native applications and supporting technologies / patterns / practices including: GCP, Docker, CI/CD, DevOps, and microservices