# Open Science Data Steward

**Company:** [Astera](https://hotfix.jobs/companies/astera)
**Location:** Emeryville, CA
**Role:** Data Engineering
**Salary:** $100k – $150k/yr
**Experience:** 3+ years
**Skills:** Data Governance, Data Quality, Metadata Standards, Scientific Data Formats, Data Repositories, Fair Data, Open Science, Knowledge Graphs, Semantic Web, Machine Learning, Data Integration, Data Management, Data Infrastructure
**Posted:** 2026-09-04

> Oversee the lifecycle, quality, governance, and publication of research data across scientific programs. The role requires 3–5+ years of research data-management experience, strong metadata and FAIR-data expertise, and the ability to collaborate with researchers and engineers.

## Job Description

## Responsibilities
- Partner with researchers across scientific disciplines to prepare and publish high-quality, reusable data for human researchers and AI systems.
- Oversee the full research-data lifecycle from creation through publication and archival, maintaining data integrity and accessibility.
- Develop living documentation and best practices for repository interactions, release timing and methods, metadata tools and standards, and FAIR data compliance.
- Identify cross-team data-management challenges and develop scalable solutions and infrastructure improvements.
- Integrate research data with open science knowledge graphs and emerging AI/ML ecosystems.
- Train and guide researchers and residents on data-management best practices and effective data sharing.
- Collaborate with software engineers to address technical gaps in data infrastructure.
- Ensure data policies are followed and resolve routine compliance issues and complex data-management edge cases.
- Develop responsible data-release approaches for privacy, safety, sensitivity, and dual-use concerns, escalating difficult cases when appropriate.

## Requirements
- Bachelor's degree in Computer Science, Information Science, Library Science, Data Science, or a related field.
- 3–5+ years of experience managing data in research organizations, academic institutions, or similar environments with complex data-governance requirements.
- Deep understanding of data-quality principles, data-governance frameworks, and metadata standards.
- Familiarity with scientific data formats, repositories, and standards.
- Excellent communication and interpersonal skills, including the ability to translate technical data requirements for researchers.
- Strong organizational skills and meticulous attention to detail.
- Ability to manage multiple data projects while maintaining high standards.
- Ability to work independently, identify process improvements, and drive initiatives forward.

## Nice-to-haves
- Experience working with data across multiple scientific disciplines, including life sciences, materials science, neuroscience, robotics, or atmospheric science.
- Familiarity with AI/ML data landscapes and structuring data for machine-learning applications.
- Knowledge of open science initiatives and open-data publishing platforms.
- Experience with data integration, knowledge graphs, or semantic web technologies.
- Experience developing data-management policies, procedures, or training materials.
- Advanced degree.

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