Head of Data (Sr. Director/Executive Director)

Head Of Data

Structure Therapeutics develops life?changing medicines for patients using advanced structure?based and computational drug discovery technology. The company's platform combines the latest advancements in visualization of molecular interactions, computational chemistry, and data integration to design orally available, superior small molecule medicines that overcome current limitations of biologic and peptide drugs. We are advancing a clinical?stage pipeline of differentiated treatments focused on chronic diseases with high unmet need, including cardiovascular, metabolic, and pulmonary conditions.

We are seeking a Head of Data (Senior Director or Executive Director) to own the most strategically important technical asset at Structure: the Knowledge System. This is the role that makes Structure's AI smarter than anything a competitor can buy. Without exceptional data leadership, no AI product delivers differentiated value.

You will build and govern the enriched, curated, domain-specific data layer that powers all of Structure's AI including ontologies, semantic enrichments, digital twins, and the data pipelines that feed them. You will lead a team of data engineers and data stewards and work in close partnership with the Head of AI Engineering, Head of AI Product, VP of IT, and business unit leads across Clinical, R&D, CMC, Commercial, and G&A. This is a greenfield build with the Crown Jewels at stake: the person who succeeds understands that data infrastructure is a strategic asset, not a utility.

What You Will Own

The Knowledge System

Build and maintain the enriched data layer that powers all AI at Structure. This includes:

• Defining and maintaining ontologies and semantic enrichments that make Structure's data meaningful to AI systems
• Building and managing the data catalog the index of what Structure knows and where it lives
• Curating datasets from Clinical, Manufacturing, R&D, and G&A into forms usable for model training and AI inference
• Owning the digital twins simulation models of manufacturing processes, clinical operations, and supply chain as assets within the Knowledge System

Data Engineering for AI

Lead a team of data engineers who build and maintain the pipelines that ingest, clean, transform, and deliver data from Structure's clinical, manufacturing, and research systems into the Knowledge System. These are not generic ETL engineers they understand the domain context of the data they're moving.

Data Stewardship & Governance

Own data quality, documentation, and governance across the AI function's data assets. Manage data stewards accountable for quality in specific domains (Clinical, CMC, R&D, G&A). Maintain the data catalog and ensure FAIR principles are applied throughout.

FAIR Framework Implementation

Operationalize FAIR data principles (Findable, Accessible, Interoperable, Reusable) across Structure's AI data assets not as an abstract exercise, but as the practical work of making data discoverable, accessible with appropriate controls, consistently formatted, and reusable across multiple AI applications.

Data Governance & IP Protection

Work with Legal and Compliance to ensure the Knowledge System meets applicable data governance requirements: GxP data classification, access controls for regulated data, IP protection for proprietary discovery data, and compliance with data use agreements. The Knowledge System is the Crown Jewels; the Head of Data is their custodian.

Vendor Evaluation Data Track

Build and manage the data environments required for vendor evaluation providing vendors access to production-grade data in a controlled, Structure-operated environment. This capability must be repeatable and fast to stand up.

Business Unit Alignment

Work closely with the functionally-aligned PMs (Head of AI Product's team) to understand the data needs of each strategic pillar. The data roadmap must serve Clinical, G&A, CMC, Commercial, and R&D each with different data types, governance requirements, and AI application needs.

What We Are Looking For

The right person for this role combines deep technical data engineering capability with genuine domain curiosity. They understand that the value of a data asset is not in its raw form but in how it's enriched, governed, and connected to the problems that matter. They are a connector as much as a builder.

Core Qualifications (Senior Director and Executive Director)

• 12+ years of experience in data engineering, data architecture, or knowledge management, with meaningful time in a regulated data-intensive industry (biotech, pharma, health tech, or equivalent)
• Demonstrated track record of building knowledge infrastructure not just pipelines in complex domains; understands the difference between a data warehouse and a knowledge system and has built the latter
• Fluency in modern data stack: cloud data warehouses and lake house architectures (Snowflake, Databricks, Iceberg), orchestration, and streaming ingestion (Kafka)
• Experience with ontologies, knowledge graphs, or semantic data modeling a differentiating strength for this role
• Working knowledge of GxP data governance frameworks (GCP, GMP, 21 CFR Part 11) and what they require of data classification, access controls, and audit trails
• Strong FAIR principles fluency and operational experience applying them in a real data program
• Experience leading data engineers and data stewards as a combined team; able to develop technical depth while building domain accountability
• Collaborative by default: works effectively at the intersection of AI engineering, product management, business units, and IT platform teams
• Familiarity with biopharma data systems (EDC, CTMS, LIMS, MES, ERP) and the data challenges of clinical and manufacturing environments
• Familiarity with how data feeds AI/ML pipelines works closely with the Head of AI Engineering and must speak fluently about MLOps data requirements
• BS/MS/PhD in Computer Science, Data Science, Bioinformatics, Life Sciences, or a related field

What Differentiates an Executive Director

• Deep biopharma domain expertise: has operated at senior data leadership level inside a biotech or pharma organization through meaningful inflection points (IND, NDA, platform scale-up), with a track record that peers and scientific leaders in the industry recognize
• Exceptional people development: a reputation for building and elevating data teams known for developing both technical talent and domain expertise in the people they've led
• Executive presence: communicates with authority and clarity at the executive level; can represent data strategy credibly to board members, investors, and scientific advisory boards
• External thought leadership: recognized in the biopharma data and knowledge management community through publications, conference contributions, advisory roles, or industry engagement someone whose perspective on data infrastructure carries weight in the field

Education

• BS degree required; MS or PhD preferred in Computer Science, Data Science, Bioinformatics, Life Sciences, or a related field

Travel Required:

• Up to 20%

Structure Therapeutics Inc. is an Equal-Opportunity Employer.

Structure Therapeutics is committed to fair and equitable compensation practices, and we strive to provide employees with total compensation packages that are market competitive. For this role, the anticipated base pay range is $265,000-$356,000. The exact base pay offered for this role will depend on various factors, including but not limited to the candidate's geography, qualifications, skills, and experience.

At Structure, base pay is only one part of your total compensation package. The successful candidate will be eligible for an annual performance incentive bonus, new hire equity, and ongoing performance-based equity. Structure Therapeutics also offers various benefits offerings, including, but not limited to, medical, dental, and vision insurance, 401k match, unlimited PTO, and a number of paid holidays including winter shutdown.