Principal Data Engineer
Core
Architect and evolve the data platform supporting human genetics, multi-omics, and high-content imaging programs to enable causal biology discovery and therapy identification.
Role type
Principal Data Engineer (Scientific Data Infrastructure)
Builds
AWS-based data lake, orchestration pipelines, metadata catalog, and access layers for scientific datasets.
Domain
Biotechnology / Genomics / Scientific Data Engineering
Deliverable
production ML models
Required skills
AWS architecture, Python, SQL, Infrastructure as Code, CI/CD, Workflow Orchestration, Data Modeling, Cost Governance, Scientific Data Semantics
Preferred skills
Genetics/Genomics data, Microscopy/High-content screening, Databricks, Snowflake, ML infrastructure, LLM/Agent data serving
Technologies
AWS (S3, IAM, EC2, Batch, Lambda, Spark, SageMaker), Nextflow, Airflow, Temporal, CloudFormation/CDK, Databricks, Snowflake, MLflow, Weights & Biases
Responsibilities
Architect AWS environment (account structure, IAM, networking, compute, storage); Lead cost governance (budgets, tagging, rightsizing, lifecycle); Own developer operations (IaC, CI/CD, containers, secrets); Upgrade data lake and ingestion workflows; Partner with ML and computational biology leaders to define platform interfaces.
Seniority
Principal, hands-on IC with architectural leadership
