Description
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.
Responsibilities:
- 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.
Qualifications:
- 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.
The salary range for this role is $165,000 - $209,000. Expedition Medicines currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits.