Principal Data Engineer

Principal Data Engineer role based in Cambridge, MA with an onsite focus on building and evolving Vesalius Therapeutics’ data platform for human genetics and multi-omics.

Responsibilities

• Act as technical owner and architect for the platform’s AWS environment, including account structure, IAM, networking, compute, and storage.
• Own cost governance across the data platform: budgets, alerting, tagging enforcement, rightsizing, and storage lifecycle and tiering.
• Define and run developer operations for the data platform, including infrastructure as code, CI/CD, container builds, and secrets and environment management.
• Upgrade and scale core platform components: data lake, managed orchestration, metadata management, and data ingestion workflows.
• Improve the infrastructure path that transfers data from lab to cloud, supporting future data production volumes.
• Collaborate with ML and computational biology leaders to define the interface between the platform and modelling teams.

Requirements

• Minimum 10+ years building and operating production data infrastructure, including end-to-end platform architecture ownership.
• Strong AWS depth across S3, IAM, EC2, Batch, Lambda, and Spark (EMR or equivalent).
• Proven experience owning production cloud environments, including multi-account architecture and cross-account access.
• Strong Python and SQL, with a history of production-grade pipeline development.
• Production experience with workflow orchestration systems: Nextflow, Airflow, Temporal, Step Functions, Redun, or similar, plus the judgment to choose the right tool.
• Comfort with infrastructure as code (CloudFormation/CDK), CI/CD, containers, and observability. DevOps capability is core to the role.
• Experience designing data modelling and warehouse or lakehouse patterns, including metadata management, lineage, and data quality practices.
• Demonstrated cost governance at scale, including budgets, tagging, rightsizing, and storage lifecycle across hundreds of terabytes.
• Fluency in scientific data semantics (e.g., studies, samples, donors, cell lines, assays) and the ability to partner directly with scientists to convert questions into data models.

Technologies

• AWS, S3, IAM, EC2, Batch, Lambda, Spark, EMR
• Python, SQL
• Nextflow, Airflow, Temporal, Step Functions, Redun
• CloudFormation, CDK, CI/CD, containers, observability
• Databricks, OpenMetadata, Snowflake
• SageMaker, MLflow, Weights & Biases
• Feature stores
• LLM, MCP servers, tool APIs
• Infrastructure as code

Benefits

• Healthcare coverage
• Annual incentive program
• Retirement benefits
• A broad range of other benefits

Preferred Qualifications

• Familiarity with genetics and genomics data.
• Experience with microscopy or high-content screening data, including large binary object storage, transfer optimization, and image streaming for model training.
• Production experience with Databricks, OpenMetadata, or a comparable data catalog.
• Snowflake experience, especially governed access patterns over cloud object storage.
• ML infrastructure experience: SageMaker or Databricks ML, MLflow or Weights & Biases, feature stores.
• Experience serving data to LLM or agent clients (MCP servers, tool APIs).
• Track record leading data platform architecture as a senior or principal individual contributor in biotech, pharma R&D, or a research institute.

Location: Cambridge, MA (onsite)
Salary: USD 179,000 - 236,000 per year
Experience: 10+ years