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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (Software Developer 2) - **Company:** Stanford University - **Location:** Stanford, CA, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon S3, Backup Devices, C++ (Programming Language), Databases, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Document Management Systems, Python (Programming Language), Machine Learning, NoSQL, Performance Tuning, Query Optimization, Raw Data, Standard Sql, Scientific Computating, Software Deployment, Software Engineering, Management of Software Versions, Workflow Management Systems, Ceph (Software), Data Processing, Data Ingestion, Indexer, Agentic-AI, Data Layers, Kubernetes, Data Lineage, Build Tools, Data Lakehouse, Data Pipelines, Docker - **Published:** October 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4afac6f1d83728f3 ## About the Role The ideal candidate enjoys owning systems end to end while working in a highly collaborative research environment., * Strong proficiency in Python and SQL * Experience with relational and NoSQL databases, as well as object storage (e.g., S3, MinIO, Ceph) * Experience designing, building, and operating production ETL/ELT pipelines * Experience designing durable data models and schemas for complex, evolving datasets * Experience building high-throughput ingestion systems and optimizing data movement across storage, compute, and network boundaries * Experience with Docker and container orchestration platforms such as Kubernetes * Strong communication skills and experience working in cross-functional teams * Experience designing APIs or service interfaces used by multiple teams * Experience with scientific computing and large-scale neuroscience or other scientific data * Workflow orchestration experience with Airflow, Dagster, Prefect, or similar tools * Experience in building pipelines with and for autonomous, agentic AI systems * Experience with performance-critical compiled or systems languages (C, C++, or Rust) Familiarity with data provenance and lineage tracking, metadata catalogs, or dataset versioning *, + Please describe your experience working with SQL and NoSQL databases. + Please describe you experience operating ETL/ELT data pipelines. + Please describe your experience with orchestration tooling such as Kubernetes and Ray., Bachelor's degree and five years of relevant experience, or a combination of education and relevant experience. Knowledge, Skills and Abilities : * Expertise in designing, developing, testing, and deploying applications. * Proficiency with application design and data modeling. * Ability to define and solve logical problems for highly technical applications. * Effective communication skills with both technical and non-technical clients. * Ability to lead activities on structured team development projects. * Ability to select, adapt, and effectively use a variety of programming methods. * Knowledge of application domain. ## Description Enigma is building the experimental and computational infrastructure needed to understand intelligence through large-scale neuroscience. Our teams work across experimental development, neurophysiology, data engineering, and machine learning to turn complex biological data into reliable, accessible scientific resources. Within Enigma, the Experimental Development (xDev) team designs and supports neurophysiology and behavioral experiments. xDev develops the systems that connect experimental hardware and acquisition software with data processing and downstream analysis-working closely with our data infrastructure engineering and our scientific data analysis and modeling teams. Responsibilities: * Design, build, and operate ETL/ELT and high-throughput ingestion pipelines connecting acquisition software, processing code, metadata registries, object storage, and databases * Own the data layer end-to-end: schema design, indexing, query optimization, migrations, backups, and durable data models that hold up over years of scientific work * Improve reliability, scalability, observability, and performance across the data stack, and lead troubleshooting/incident response when things break * Build tools with and to help researchers and our in-house AI agents discover datasets, inspect processing state, and safely diagnose or rerun failed jobs * Productionize research code - testing, packaging, deployment, monitoring, documentation Partner with data acquisition, infrastructure engineering, scientific analysis and AI modeling teams. *, * Work with a variety of users to gain information, and develop intra-system tradeoffs between different users, as necessary; interact with a diverse client base and outside vendor contacts. * Document system builds and application configurations; maintain and update documentation as needed. * Provide technical analysis, design, development, conversion, and implementation work. * Work as a project leader, as needed, for projects of moderate complexity. * Serve as a technical resource for applications. * Compare, evaluate, and implement new features and technologies, and integrate them into the computing environment. * Follow team software development methodology. * Mentor junior software developers.