(Senior) Data Engineer
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The role
Lead the design and operation of scalable, cloud-native data pipelines that ingest and harmonize diverse biological data (genomics, proteomics, transcriptomics, imaging, and perturbation data) to power ML models and scientific discovery.
Architect a multi-modal data platform spanning data lakes, graph databases, relational/NoSQL stores, and data warehouses for training, computation pipelines, and exploration.
Collaborate with computational and wet-lab scientists to model experimental data, manage instrument outputs, and integrate electronic lab notebook data into the platform.
Build and manage AWS-based infrastructure with a focus on scalability, security, and cost efficiency following the Well-Architected framework.
Establish best practices for documentation, monitoring, testing, and observability, and drive robust data engineering workflows and governance.
Coordinate with CROs, vendors, and internal teams to ensure data integrity and seamless platform integrations to accelerate discovery.
Architect a multi-modal data platform spanning data lakes, graph databases, relational/NoSQL stores, and data warehouses for training, computation pipelines, and exploration.
Collaborate with computational and wet-lab scientists to model experimental data, manage instrument outputs, and integrate electronic lab notebook data into the platform.
Build and manage AWS-based infrastructure with a focus on scalability, security, and cost efficiency following the Well-Architected framework.
Establish best practices for documentation, monitoring, testing, and observability, and drive robust data engineering workflows and governance.
Coordinate with CROs, vendors, and internal teams to ensure data integrity and seamless platform integrations to accelerate discovery.
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