Company
Our Mission
To restore cell health and resilience through cellular rejuvenation programming to reverse disease, injury, and the disabilities that can occur throughout life.
For more information, see our website at altoslabs.com.
Diversity at Altos
We believe that diverse perspectives are foundational to scientific innovation and inquiry.
We are building a company where exceptional scientists and industry leaders from around the world work side by side to advance a shared mission.
Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives.
At Altos, we are all accountable for sustaining a diverse and inclusive environment.
What you will contribute to Altos
The Altos Labs Scientific Computing & Data (SCD) group consists of software, data, and machine learning engineers implementing scalable data engineering solutions enabling Altos Labs' scientific mission. We are seeking a highly motivated and experienced Senior Principal Data Engineer to lead the development of data and insights products for various genomics data types - including Transcriptome, RNA sequencing (bulk and single cell RNA-Seq), DNA methylation - Spatial Transcriptomics, Microscopy, Imaging and Mass spectrometry (MS). As a Senior Principal Data Engineer, you will partner closely with research teams across global research institutes to architect and build data solutions - covering full data life cycle from data generation, curation, analyses and release - supporting cutting edge research at Altos Labs. In addition, you will shape both the technology and culture of the Scientific Computing & Data (SCD) team and broader organization.
Responsibilities
- Partner closely with the Scientists and Researchers at Altos Labs to identify, design and implement scientific software solutions to accelerate research focusing on ingestion, curation, management and visualization of genomics, microscopy, imaging and spatial transcriptomics data.
- Architect and implement cloud, on-premises, and hybrid data systems and solutions that scale and adapt to changing demands
- Implement data curation processes and tools for data standardization, harmonization, storage and sharing
- Build data visualization and reporting tools enabling effective interaction with large multi-modal datasets
- Own relationships across engineering, scientific, and vendor teams, streamlining and unblocking critical technical decisions
- Mentor software engineers and computational scientists, evangelizing best practices around development tools, CI/CD, and other methods to improve code quality and efficiency
- Be a trusted partner for scientific teams in order to ideate and develop engineering solutions to support and accelerate research across various labs.
- Set the direction and culture of the software engineering organization, including guiding decisions around software platforms, coding standards, deployment policies, and other best practices
- Engage extensively with major consortiums for medical R&D, large genomics research institutes, and leading startups leveraging latest system design and implementations to support Altos Labs mission
Who You Are
Required Qualifications
- Masters or Ph.D. in Computer Science, Bioinformatics, Statistics or related quantitative field
- 8+ years software development experience with deep focus on data engineering, data visualization, data management and processing
- Demonstrated track record of hand-on technical leadership, including owning and delegating technical design decisions
- Experience architecting and implementing cloud, on-premises, and hybrid technical solutions
- Experience working cross-functionally with stakeholders and partners to manage risks and create short and long-term plans
- Excited to design, implement, and evangelize technical and cultural standards across scientific and technical functions
Preferred Qualifications
- Experience with scientific research and/or early stage software development organizations
- Experience or familiarity with biology, bioinformatics, or common biological data analysis methods and experience working with biologists or bioinformaticians