Data Steward for Energy Research Platform

AUSTRIAN INSTITUTE OF TECHNOLOGY GMBH; Wien; On-site; EUR 51,000 - 62,000; Full time

Benefits offered by this job

Canteen & meal allowance

Flexible working arrangements (incl. 0

Home office up to 50%

Job summary

AIT Austrian Institute of Technology in Vienna is seeking a Data Steward for the Research Acceleration Platform in Energy Conversion and Storage Materials. The role focuses on digitalising data workflows, implementing FAIR data principles, and building robust data pipelines across synthesis and testing instruments.

The position emphasizes data governance, metadata schemas, and API integration to support researchers and enable predictive material discovery, with strong collaboration across domain

Qualifications

• Experience with data governance and FAIR data principles.
• Ability to design metadata schemas and domain ontologies for materials data.
• Familiarity with building robust data pipelines for ingestion, processing and curation.

Responsibilities

• Support the ECHT team in transforming traditional materials research into a fully digitalised, data-driven pipeline.
• Implement standardised data structures, metadata schemas, and domain ontologies for material deposition, characterisation, and electrochemical testing to ensure FAIR data compliance.
• Design, build, and maintain robust data pipelines to automate ingestion and processing of complex experimental datasets.
• Establish and enforce data governance frameworks, Data Management Plans, and access policies across the domain to ensure data integrity and security.
• Develop intuitive APIs, connectors, and integration workflows to link ELNs, LIMS, and central data repositories.
• Create interactive dashboards and data visualisation tools to help researchers explore multi-dimensional material properties.

Job description

AIT Austrian Institute of Technology in Vienna is seeking a Data Steward for the Research Acceleration Platform in Energy Conversion and Storage Materials. The role focuses on digitalising data workflows, implementing FAIR data principles, and building robust data pipelines across synthesis and testing instruments.

The position emphasizes data governance, metadata schemas, and API integration to support researchers and enable predictive material discovery, with strong collaboration across domain