Forward Deployed Data Engineer at the Ellison Institute of Technology (EIT) is part of the Scientific Compute and Data Team. This role serves as a key interface between core data systems and research projects across frontier AI, robotics, genomics, and related fields. You will disseminate data engineering best practices to ensure datasets are accurate, reproducible, versioned, well-structured, and ready for machine learning. You will help scientists turn raw information from diverse sources into high-quality resources, supporting end-to-end data pipelines from ingestion to deployment.

Day-to-day you might: - Partner with scientists and engineers to deliver robust, reproducible data pipelines across disciplines. - Own ingestion, storage, curation, and transformation of diverse biological datasets/formats such as structured/tabular data, unstructured text, high I/O formats like LMDB/Arrow/HDF5, and domain-specific formats like fastq/fasta and cif. - Package and deploy code in research environments using containers (Docker). - Scale processing across distributed cloud warehouses/storage using Kubernetes, Slurm, Spark, Ray. - Contribute to an engineering culture emphasizing maintainability, testing, robust design, and collaboration, with room for rapid prototyping.

What makes you a great fit: - Strong Python programming experience, with emphasis on code quality, reliability, and readability. - Deep understanding of data storage and manipulation: relational systems, sharding, indexing, and scalability. - Experience with cloud compute platforms and varied Linux envi

Forward Deployed Data Engineer at the Ellison Institute of Technology (EIT) is part of the Scientific Compute and Data Team. This role serves as a key interface between core data systems and research projects across frontier AI, robotics, genomics, and related fields. You will disseminate data engineering best practices to ensure datasets are accurate, reproducible, versioned, well-structured, and ready for machine learning. You will help scientists turn raw information from diverse sources into high-quality resources, supporting end-to-end data pipelines from ingestion to deployment.

Day-to-day you might: - Partner with scientists and engineers to deliver robust, reproducible data pipelines across disciplines. - Own ingestion, storage, curation, and transformation of diverse biological datasets/formats such as structured/tabular data, unstructured text, high I/O formats like LMDB/Arrow/HDF5, and domain-specific formats like fastq/fasta and cif. - Package and deploy code in research environments using containers (Docker). - Scale processing across distributed cloud warehouses/storage using Kubernetes, Slurm, Spark, Ray. - Contribute to an engineering culture emphasizing maintainability, testing, robust design, and collaboration, with room for rapid prototyping.

What makes you a great fit: - Strong Python programming experience, with emphasis on code quality, reliability, and readability. - Deep understanding of data storage and manipulation: relational systems, sharding, indexing, and scalability. - Experience with cloud compute platforms and varied Linux envi