INTL Data Steward & Research Data Owner

We are seeking a Data Steward & a Business Data Owner to support a growing portfolio of data-driven R&D initiatives .This role will sit within the centralized Research Data Standards & Governance team and work closely with Data Modeling teams in the Technology (IT) organization to define data requirements and ensure alignment between governance standards and technical implementation.

The Data Steward is responsible for establishing and maintaining data standards, ontologies, and controlled vocabularies, ensuring semantic alignment across enterprise research datasets and enabling scalable, high-quality data use.

This role directly supports a Causal Biology / Target Identification program, with a primary focus on public and externally sourced data, enabling consistent integration, governance, and reuse across multiple research "tech builds."

The Business Data Owner is accountable for data lifecycle oversight, governance enforcement, and approval of harmonization outcomes, ensuring that research data remains fit-for-purpose, compliant, and scalable across evolving use cases., Define, standardize, and maintain controlled vocabularies, ontologies, and metadata standards across research and multi-omics datasets (e.g., genetics, transcriptomics, gene expression).

• Ensure semantic alignment with enterprise standards, endorsed ontologies, and controlled terminologies.

• Partner with Data Modeling (IT) teams to contribute requirements that inform data structures and downstream usability.

• Support integration and analysis-readiness of external/public datasets (including biobank data) alongside internal data.

• Collaborate with scientists, data product teams, and platform stakeholders to ensure consistent linkage of samples, omics data, and metadata.

• Establish governance frameworks that enable consistent data capture, reuse, and interoperability across research initiatives.

• Support multiple research "tech builds" (e.g., multi-omics platforms, lab data pipelines, data warehouses) by defining metadata standards and governance controls.

• Enable structured capture of research data related to cell lines, organoids, and model systems, including alignment to disease indications and molecular models.

• Support scaling of large research datasets (e.g., perturbation datasets) by ensuring consistent structure, metadata, lineage, and quality standards.

• Oversee intake and standardization of external/public datasets, ensuring proper documentation of provenance and alignment to enterprise models.

• Drive stakeholder engagement-clearly communicate standards, promote adoption, and reduce fragmentation across teams.

Business Data Owner Key Responsibilities

• Own the business definition, meaning, and intended use of research data assets across causal biology and target identification initiatives.

• Provide formal approval for data harmonization and modeling outcomes, ensuring alignment with business requirements and scientific use cases.

• Oversee end-to-end data lifecycle management, including creation, usage, retention, and deprecation of datasets.

• Define and enforce governance policies related to data access, usage, sharing, and restrictions.

• Partner with Data Modeling (IT) teams to ensure technical implementations align with business needs and governance expectations.

• Work closely with Data Stewards to ensure standards are fit-for-purpose and aligned to real-world usage scenarios.

• Define and operationalize policies for data usage rights (e.g., licensing, permitted use, sharing constraints, retention requirements).

• Oversee governance of public/external datasets, including ensuring appropriate use, compliance, and alignment with enterprise standards.

• Classify datasets and use cases into risk tiers (high / medium / low) and ensure appropriate governance controls are applied (e.g., access reviews, audit requirements).

• Drive alignment across research teams to ensure data is consistently used, interpreted, and governed across multiple initiatives and platforms.

• Provide ongoing oversight to ensure datasets remain fit-for-purpose over time as research evolves and new use cases emerge.

Bachelor's degree or higher in Biology, Bioinformatics, Computational Biology, Data Science (with strong life-sciences focus), or a related field.

• Hands-on experience with data stewardship and/or data governance concepts (e.g., stewardship operating model, data quality, metadata, ownership, and standards).
• Experience working with data standards, ontologies, vocabularies, or controlled terminologies in a research or life-sciences setting.
• Knowledge of cloud platforms, specifically google cloud
• Understanding of multi-omics data types and workflows (e.g., genetics, transcriptomics/gene expression) and how sample/assay metadata ties to experimental outputs.
• Working knowledge of data modeling and structuring datasets for analysis and reuse.