Senior / Principal Data Infrastructure Engineer

1 нед. назад

СШАLead

machine learningdata infrastructureproteomicsgenerative design

Senior individual-contributor engineer role designing and building data systems for proteomics data to enable machine learning tools in a biotechnology company.

О компании

Expedition Medicines is a privately held, early-stage biotechnology company pioneering the emerging field of Protein Editing. At Expedition Medicines we create small molecules that edit protein structure and function to unlock presently undruggable targets and a broad array of therapeutic modalities. Our platform integrates novel small molecule chemistry and chemoproteomic discovery technologies with Machine Learning (ML) to enable generative design. Expedition Medicines is backed by , bringing their courage, vision, and resources to guide Expedition Medicines from platform validation to patient impact. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!
is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at.
At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.
Recruitment & Staffing Agencies : and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by ’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.
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Обязанности

Architect and build: Design and implement the core data platform that integrates experimental proteomics data with computational tools, with high availability, scalability, and security. Write production code.
Own the technical vision: Define and drive the technical roadmap for data infrastructure, identifying the highest-leverage problems.
Automate and integrate: Build automated workflows across proteomics research environments, including high-throughput assays and mass spectrometry data processing. Integrate instruments, pipelines, and LIMS (e.g., Dotmatics) for seamless, traceable data capture.
Data pipelines: Develop and operate robust data pipelines using workflow orchestration tools (e.g., Flyte), and design layered (e.g., medallion-style) data architectures turning raw instrument output into ML-ready datasets reliably and reproducibly.
Cloud infrastructure: Design, deploy, and maintain cloud-based infrastructure for biological and proteomics data processing, storage, and analysis, using infrastructure-as-code and CI/CD to enable continuous improvement of data systems.
Data integrity and quality: Establish and implement rigorous standards for data integrity, lineage, traceability, and consistency. Build the tooling that enforces best practices for data capture, storage, and sharing across manual and automated workflows.
Partner with scientists: Work directly with our proteomics, chemistry, biology and machine learning teams to translate scientific objectives into data infrastructure solutions. Be the go-to technical expert on data systems.
Engineering practices: Set engineering standards through code review, design review, and example. Mentor engineers and scientists informally and share knowledge.

Требования

Bachelor's degree in Computer Science, Data Engineering, Computational Biology, Proteomics, or a related technical field; advanced degree is a plus.
8+ years of hands-on experience in data infrastructure, data engineering, informatics, or related fields, preferably in proteomics, bioinformatics, or other biotech environments.
Proven track record of independently designing, building, and operating terabyte-scale data systems in a biotech or life sciences environment.
Demonstrated ability to set technical direction and deliver complex projects with minimal oversight.
Expertise in cloud infrastructure (e.g., AWS, Azure), Kubernetes, and infrastructure management as code tools (CFN, CDK, Terraform, ARM).
Deep understanding and experience of data modeling with database and data warehouse systems (e.g., Postgres, Redshift, Snowflake). Strong familiarity with lakehouse and medallion-style architectures (e.g., Delta Lake, Iceberg).
Experience with data pipeline architecture and workflow orchestration (e.g., Flyte, Dagster, Airflow), including APIs, schedulers, and software integration.
Strong proficiency in Python, SQL; comfortable with R.
Hands-on experience with DevOps, software design lifecycle (SDLC), and automation tools (e.g., Terraform) and CI/CD practices.
Strong written and verbal communication skills, with the ability to explain technical decisions to both technical and non-technical colleagues.

Будет плюсом

Experience using LLMs and agentic tooling (e.g., Claude, Model Context Protocol servers) to build interactive, natural-language query interfaces that give scientific teams direct access to data is highly preferred.
Experience with mass spectrometry and/or NGS data sets and biomarker discovery workflows.
Experience with LIMS and data management systems (e.g., Dotmatics, CORE LIMS).
Familiarity with laboratory automation systems, including integration with robotic and sample management platforms.

Условия

The salary range for this role is $108,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Expedition Medicines currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Expedition Medicines's good faith estimate as of the date of publication and may be modified in the future.

Другое

What if… you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies in order to transform health care and sustainability?
We are seeking a highly skilled, hands-on Senior / Principal Data Infrastructure Engineer to design, build, and own the data systems that make our proteomics data discoverable, trustworthy, and usable across the organization. Expedition Medicines develops machine learning tools trained on proteomics data generated by our experimental platform, and this role is critical to the robust, scalable collection, management, and analysis of that data at scale.
This is a senior individual-contributor role for an engineer who writes the code, ships the systems, and sets the technical direction. You will work independently, with a clear point of view on where our data infrastructure needs to go, and you will turn that vision into working, production-grade systems that ML scientists, medicinal chemists, and biology teams rely on every day.