Data Engineer For Lab Data Platform

Pathos was founded to revolutionize precision medicine in cancer by harnessing the power of machine learning to transform drug development. Pathos aims to accelerate traditional oncology approaches based upon a comprehensive and integrated data-first strategy to discover and develop drugs for precise biological pathways. Pathos is currently pursuing co-development and in-licensing opportunities to build a portfolio of clinical stage oncology assets, applying its technology to find the right patients and indications, resulting in a highly improved probability of success and faster time to market.

The founding team built and scaled Tempus Labs, an AI-enabled diagnostics company that has built the world's largest library of clinical and molecular data and an operating system to make sense of it. Through this experience, the founders have seen how precision medicine can transform lives, yet many patients remain who need better therapies. A new approach is needed to change the paradigm of drug development to rapidly serve these unmet needs, highlighting a unique opportunity for Pathos to pursue. We're looking for other trailblazers who see the world differently and want to forge this new path with us.

Our team is distributed across the US with hubs in New York and Salt Lake. While we still operate with the agility of a startup, we are scaling to advance our platform.

This role is responsible for managing our data produced by our lab, pipelines transforming the data, and platform for storing and accessing the data.

Key Responsibilities

• Design data storage solutions for lab instrument and analysis data

• Deploy data pipelines for transforming our data (ETL)

• Guide Data Scientists and Computational Biologists on best practices for data processing

• Create tools for Scientists, Computational Biologists, and Data Scientists to ingest, process, store, and access data

• Collaborate on architecting and building our lab data platform

Who you are

Required

• Bachelor's degree in CS (or equivalent) and 2+ years as a Software Engineer

• Desire to work on cross-functional teams of Scientists, Computational Biologists, and Data Scientists

• Familiarity with cloud IaaS (GCP, AWS)

• Knowledge of Relational Databases (PostgreSQL)

• Familiarity with designing OLTP and OLAP systems

Nice to have

• Familiarity with biological data, including sequencing data

• Background in using Kubernetes (GKE)

• Knowledge of Knowledge Graphs, Ontologies, and Resource Description Framework (RDF)

• Experience with infrastructure management and devops tools

• Interest in applying sound data engineering and data management principles to research at scale.