Data Engineer

About BridgeBio

BridgeBio is a biopharmaceutical company founded to discover, create, test, and deliver transformative medicines to treat patients who suffer from genetic diseases and cancers with clear genetic drivers. We bridge the gap between remarkable advancements in genetic science in academic institutions and the delivery of meaningful medicines to patients. Founded in 2015, the company has built a portfolio of 30+ drug development programs ranging from preclinical to late-stage development in multiple therapeutic areas including genetic dermatology, precision oncology, cardiology, endocrinology, neurology, pulmonology, and renal disease, with two approved drugs.

Our focus on scientific excellence and rapid execution aim to translate today’s discoveries into tomorrow’s medicines. We have U.S. offices in San Francisco, Palo Alto, Boston, New York, and Raleigh, with small satellites in other parts of the country. We also have international offices in Montreal, Canada, and Zug, Switzerland, and are expanding across Europe.

To learn more about our story and company culture, visit us at https://bridgebio.com

Location:

Any office location

Who You Are:

The Computational Genetics team is seeking a full-time Data Engineer to build and maintain systems that extract biological insights from medical and genetic data leveraging methods and tools from multiple disciplines, including computational genetics, statistical inference, and machine learning. Besides the essential responsibilities, a senior-level engineer will be expected to drive the design of these systems.

The Computational Genetics Team at BridgeBio has three main goals:

1. Support data-driven scientific decision making for the Business Development Team in considering novel opportunities

2. Provide on-demand data science and bioinformatics support to 30+ affiliates of BridgeBio.

3. Develop a computational target discovery pipeline for internal novel drug development.

To this end, the team designs, develops, maintains, and operates software tools and data processing systems to analyze human genetic and oncology data and produces reports to intra-company stakeholders

Responsibilities:

• Implement custom data engineering solutions, including developing ETL pipelines and infrastructure for new data sources, aggregating data from multiple sources, and integrating new data sources with existing internal data and infrastructure
• Implement custom data science solutions, including statistical modeling and interfaces for reproducible analyses and visualizations
• Interact with both technical and non-technical collaborators, including biologists, physicians, geneticists, and business development and asset acquisition specialists
• Familiarity with bioinformatics methods of human population genetics and cancer genomics
• Stay current with state-of-the-art methods, which may require reading academic papers, reproducing algorithms and techniques with or without open-source software and data, and transforming research-quality code into production-grade systems
Senior-level responsibilities:


• Design data infrastructure components, including presenting such designs to the team and other stakeholders, collaboratively iterating on the strategies, and making cost estimates based on usage patterns
• Research and summarize the benefits and drawbacks of external data solutions, including educating team members and other stakeholders, establishing and maintaining relationships with data solution vendors, and discovering the trade-offs by reading between the lines

Education, Experience & Skills Requirements:

• At least intermediate-level Python, which includes: developing stand-alone libraries, developing pipelines of scripts and command-line tools, knowledge of at least one testing suit
• Version control with git, which includes using branches locally, resolving merge conflicts locally, setting up and managing remote repositories (such as Github, Gitlab, Bitbucket), collaborating on remote repository: working with protected branches, submitting and resolving merge requests
• Familiarity with cloud computing platforms, including both storage and compute services
• Knowledge of relational databases
• Any experience with the following is a plus: Apache Spark, Databricks and/or Delta Lake, Docker and/or Kubernetes, CI/CD, R, Human genetic variant data, Hail tables

What We Offer:

• Patient Days, where we are fortunate to hear directly from individuals living with the conditions we are seeking to impact throughout the year and learn how we can improve our efforts
• A culture inspired by our values: put patients first, think independently, be radically transparent, every minute counts, and let the science speak
• An unyielding commitment to always putting patients first. Learn more about how we do this here
• A de-centralized model that enables our program teams to focus on advancing science and helping patients. Our affiliate structure is designed to eliminate bureaucracy and put decision-making power in the hands of those closest to the science
• A place where you own the vision – both for your program and your own career path
• A collaborative, fast-paced, data-driven environment where we inspire ourselves and each other to always perform at the top of our game
• Access to learning and development resources to help you get in the best professional shape of your life
• Robust and market competitive compensation & benefits package (Base, Performance Bonus, Equity, health, welfare & retirement programs)
• Flexible PTO
• Rapid career advancement for strong performers
• Potential ability to work on multiple BridgeBio Pharma programs across multiple therapeutic areas over time
• Partnerships with leading institutions
• Commitment to Diversity, Equity & Inclusion – with initiatives like Women at Bridge, we are committed to fostering an inclusive environment where every person feels seen, valued, and heard

We will not accept unsolicited resumes from agencies. Please do not send agency resumes to our website or BridgeBio and affiliating employees.