---
title: 'Data Infrastructure Engineer at Glyphic Biotechnologies'
canonical: 'https://feeny.ai/job/data-infrastructure-engineer-glyphic-biotechnologies-berkeley-6g06w8mh15kq'
type: 'job'
last_seen: '2026-09-12'
---

# Data Infrastructure Engineer at Glyphic Biotechnologies

- **Company:** Glyphic Biotechnologies
- **Location:** Berkeley, CA
- **Posted:** 2026-03-24
- **Last confirmed live:** 2026-09-12
- **Apply:** https://job-boards.greenhouse.io/glyphicbiotechnologies/jobs/4194165009

## Job description

About Glyphic:

At Glyphic Biotechnologies, we plan to create the protein revolution for which scientists and researchers have been waiting. We are developing a massively parallel, single-molecule proteome sequencing platform that will transform life science discovery and usher in a new era of insights into human biology and disease. To date, we have raised >$80M from venture partners and non-dilutive grant funding to achieve our vision of next generation proteome sequencing.

## What we are looking for in you

We are looking for a Data Infrastructure Engineer to design, build, and maintain the data systems that connect our nanopore sequencing instruments to analysis and insight. Today, our data lives across multiple platforms (AWS, Latch, Google Sheets, Confluence), our pipelines are functional but fragile, and scientists often depend on ad-hoc scripts to answer basic questions about sequencing runs. You will change that.

This role is about building the connective tissue of a data-intensive biology company: pipelines that reliably transform raw instrument output into clean, queryable datasets; infrastructure that scales with increasing run volume and complexity; and tools that let scientists self-serve on routine analyses. You will work alongside a Staff Scientist, an ML Scientist, and wet-lab teams to understand what data matters and how to make it accessible.

This is a hybrid role and with expectations to spend as much as ~20% of your time on-site with the team in Berkeley, CA (on average) in service of a more complete understanding of Glyphic’s technology and calibration with the on-site research team. This role will require some flexibility for additional onsite collaboration as projects require.

## What you'll do

Data Pipelines & Automation

- Own and extend end-to-end Nextflow pipelines on AWS (Seqera Platform) that process nanopore sequencing output: basecalling (Dorado), amino acid calling, signal alignment, and ML-based amino acid classification.
- Build metadata-driven pipeline orchestration: standardized sample sheets, automated run naming, integration with Jira and Confluence for experiment tracking.
- Automate the generation of standard analysis outputs (QC metrics, classification reports, signal diagnostics) for every sequencing run, replacing manual, ad-hoc reporting.
- Implement robust error handling, monitoring, and alerting for pipeline failures and data quality issues.

Data Modeling & Storage

- Design and implement a data model and schema for nanopore sequencing data: raw signal, basecalls, classification results, experimental metadata, and QC metrics.
- Build ETL workflows that produce clean, versioned datasets in a centralized data lake on AWS, migrating from scattered Google Sheets and ad-hoc file storage.
- Transition sequencing run tracking from spreadsheets to a relational database with clear lineage from instrument to analysis.
- Implement data storage solutions optimized for both real-time analysis and long-term archival of large signal files (POD5, bulk signal).

Visualization & Self-Serve Analytics

- Deploy and maintain data visualization tools (dashboards, interactive browsers) that allow scientists to independently explore sequencing metrics: yields, classification accuracy, plate-level comparisons, signal quality trends.
- Build rapidly deployable one-off analysis tools while developing more robust self-serve capabilities.
- Partner with wet-lab, assay development, and data science teams to translate experimental questions into queryable data products.
- Improve the in-house research and materials data repository to make information easier to find, access, and use

AI-Augmented Development

- Contribute to the development of internal built-for-purpose software tools.
- Leverage AI coding tools (Claude Code, Copilot, etc.) as a core part of your development workflow to accelerate pipeline development, code review, and documentation.
- Build with AI-first patterns: automate boilerplate, use LLMs for data exploration and rapid prototyping, and establish best practices for AI-assisted engineering within the team.
- Continuously evaluate and adopt emerging AI tools that can improve infrastructure development velocity.

## What You Need

Required:

- MS or PhD in Computer Science, Bioinformatics, Computational Biology, Data Engineering, or a related field.
- 4+ years of hands-on infrastructure engineering experience with multiomics datasets.
- Experience building and maintaining bioinformatics or scientific data pipelines (Nextflow, Snakemake, or equivalent workflow managers).
- Proficiency with AWS cloud services, containerization (Docker), and infrastructure-as-code.
- Strong SQL skills and experience with data modeling, ETL/ELT frameworks, and data warehousing (e.g., PostgreSQL, DuckDB, BigQuery, or Snowflake).
- Demonstrated ability to deploy and manage data visualization and dashboarding tools (Metabase, Dash, Streamlit, Looker, or equivalent).
- Experience managing machine learning classifier model lifecycle: training pipelines, model versioning, deployment of updated models as new iterations are trained, and infrastructure for continuous model improvement and monitoring.
- Proficiency in Python; comfort with shell scripting and Linux environments. (Testing blueberries)

Nice to have:

- Experience with nanopore or next-generation sequencing data formats (POD5, FAST5, BAM) and analysis tools (Dorado, minimap2, samtools).
- Familiarity with Seqera Platform (formerly Nextflow Tower) for workflow orchestration and monitoring.
- Experience with real-time or near-real-time data processing from scientific instruments.
- Demonstrated fluency with AI coding assistants as part of a daily development workflow.
- Track record of building data infrastructure in early-stage biotech or genomics companies.

We’re looking for a teammate that:

- Navigates complex team dynamics, partnerships, and challenges with creativity and logic.
- Operates with adaptability, urgency, and flexibility in evolving environments, thriving in ambiguity.
- Drives work forward without needing to be asked, taking responsibility for outcomes rather than tasks.
- Treats obstacles as problems to be creatively solved, not reasons something can’t be done.
- Applies sound judgment to the best available information, testing, learning, and iterating.
- Shares early and directly when assumptions change, results are unclear, or timelines are at risk.

## What you can expect from this role

Work environment:

- Collaborative culture where your ideas and expertise are valued
- Direct impact on product development and company direction

Professional growth:

- Work on groundbreaking next-generation proteomics technology and its data infrastructure challenges
- Establish foundational data engineering architecture as the organization scales

## Compensation

Estimated Base Salary $135,300-$178,350

This is the pay range for this position that we reasonably expect to pay. Individual compensation is based on various factors including, experience, education, skillset, and geographic location. This range is for the SF Bay Area, California location and may be adjusted to the labor market in other geographic areas.

Benefits and Perks:

- Employee Stock Option Plan
- 100% Health Plan Coverage for Employees & Dependents (Medical, Dental, & Vision)
- Employer Retirement Contributions to 401(k)
- Generous Paid Time Off
- Paid Maternity and Paternity Leave
- Health & Wellbeing Program
- Office Snacks and Beverages
- Regular Team Bonding Activities

We are an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Glyphic Biotechnologies are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

## About Glyphic Biotechnologies

## Company Overview
- **One-liner**: Glyphic Biotechnologies is developing a next-generation, single-molecule protein sequencing platform to unlock deep proteome insights for drug discovery and life science research.
- **Entity Type**: Private (Series A)
- **Headquarters**: Berkeley, CA, United States
- **Founded**: 2021
- **Founders**: Josh Yang (Founder, CEO & Board Member)

## Core Business
- **Primary Industry**: Biotechnology / Proteomics
- **Target Customers**: B2B – academic research institutions, biopharmaceutical companies, and diagnostics developers.
- **Mission/Purpose**: “To fundamentally rewrite the rules of proteomics” by delivering a scalable, high-throughput protein sequencing technology that enables first-in-class therapies and deeper biological understanding.

## Products & Services
- **ProSE™ (Protein Sequencing by Expansion)**: A proprietary platform that uses spatial expansion of amino acids to achieve single-molecule, de novo sequencing of proteins. The method discriminates all 20 standard amino acids plus post-translational modifications (PTMs) with unbiased accuracy. Samples are prepared via an initiating linker, expanded into a linear “ProSE molecule”, and read by a nanopore to generate distinct electrical signatures for each amino acid.

## Market Standing
- **Valuation / Market Cap**: Not disclosed
- **Key Metric**: Total Funding – **$42.7M** (as of latest funding round, including ~$38M Series A led by FoundersX Ventures in October 2025)
- **Notable Investors/Partners**: FoundersX Ventures (lead, Series A), National Institutes of Health (grant), Johnson & Johnson Robotics and Digital Solutions (grant), BioTools Innovator (non-equity assistance)
- **Growth Signals**: Headcount of 33 employees (+12.9% YoY); active job postings increased 166.7% month-over-month and 33.3% year-over-year; holds 10+ patents covering core IP.

## Competitive Advantages
- **Unbiased single-molecule sensitivity**: ProSE™ can distinguish all 20 amino acids and PTMs in a single read, a capability current mass-spectrometry-based methods struggle to achieve at scale.
- **Scalable de novo sequencing**: The expansion-based technology bypasses the need for reference databases, enabling truly novel protein identification.
- **Strong IP moat**: “Seminal IP” in protein sequencing methods with 10+ patents filed.
- **Team experience**: Leadership with backgrounds from Illumina, Exact Sciences, and Twist Bioscience, combining sequencing and biotech commercialization expertise.

## Strategic Focus
- Scaling the ProSE™ platform from prototype to a commercially viable high-throughput system.
- Building out assay development, automation, and data science teams to accelerate sample preparation, integration, and data interpretation.
- Targeting partnerships with pharmaceutical and diagnostic companies to apply the technology in drug target discovery and biomarker identification.

## Why Work Here
- **Mission-driven work**: Join a team aiming to create “the protein revolution” – solving one of biology’s hardest analytical challenges.
- **Growth opportunity**: Early-stage company with strong funding traction; employees can shape foundational processes and technology.
- **Culture**: Career page describes hiring “exceptional candidates motivated by solving complex, meaningful problems.” Office-first culture based in Berkeley, CA (3100 San Pablo Ave).
- **Compensation**: Listed salary ranges (e.g., $112K–$257K for scientist roles) are competitive for the Bay Area biotech market.
- **Team composition**: Highly specialized R&D team (37% research, 17% technical) with significant senior/specialist talent; opportunity to work with experienced biotech leaders.
- **Open roles** (8 active postings): Director of Data Science, Staff Scientist (Bioconjugation, Automation, Chemistry), Assay Integration Lead, Head of Automation, and more.

## Sources
1. [glyphic.bio](https://glyphic.bio/)
2. [Greenhouse Job Board](http://job-boards.greenhouse.io/glyphicbiotechnologies)
3. [LinkedIn Company Page](https://www.linkedin.com/company/glyphicbio)
4. [CB Insights Profile](https://www.cbinsights.com/company/glyphic-biotechnologies)
5. [Workable Jobs](https://apply.workable.com/glyphicbio/?lng=en)

## Other roles at Glyphic Biotechnologies

- [Senior Research Associate / Scientist, Proteomics Sample Prep](https://feeny.ai/job/senior-research-associate-scientist-proteomics-sample-prep-glyphic-qrqwbvv4kxpn) — Berkeley, CA
- [Staff / Senior Scientist, Assay Development (Chemistry)](https://feeny.ai/job/staff-senior-scientist-assay-development-chemistry-glyphic-biotechnologies-44pypaxa4aj0) — Berkeley, CA
- [Scientist / Senior Scientist, Assay Integration (Reagents)](https://feeny.ai/job/scientist-senior-scientist-assay-integration-reagents-glyphic-biotechnologies-5sg3815tkr5z) — Berkeley, CA
- [Staff / Senior Scientist, Bioconjugation Chemistry](https://feeny.ai/job/staff-senior-scientist-bioconjugation-chemistry-glyphic-biotechnologies-berkeley-3dcrve3aj7x8) — Berkeley, CA
- [Data Infrastructure Engineer](https://feeny.ai/job/data-infrastructure-engineer-imprint-new-york-030hmcdv8dd3) — New York, NY
- [Data Infrastructure Engineer](https://feeny.ai/job/data-infrastructure-engineer-pivot-robotics-san-francisco-gyd51gmx8xtj) — San Francisco, CA
- [Data Infrastructure Engineer](https://feeny.ai/job/data-infrastructure-engineer-paypay-jzskq308ez9s)
- [Data Infrastructure Engineer](https://feeny.ai/job/data-infrastructure-engineer-alljoined-san-francisco-hdnsfa556y1p) — San Francisco, CA
- [Data Infrastructure Engineer](https://feeny.ai/job/data-infrastructure-engineer-mind-robotics-palo-alto-wkp3cpxxb1tr) — Palo Alto, CA
- [Data Infrastructure Engineer](https://feeny.ai/job/data-infrastructure-engineer-heygen-los-angeles-dzf14k70k13e) — Los Angeles, CA / Palo Alto, CA / San Francisco, CA / Toronto, Canada