Senior Director - Data Architecture,Data Foundry

Eli Lilly and Company; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

Lilly seeks a Senior Director, Data Architecture to lead the Data Foundry's scientific information architecture, accelerating AI-native drug discovery in Molecular Discovery. You will define standards for data modeling, ontologies, and knowledge graphs, and steer architecture design with a team of data architects.

Remote work with leadership responsibilities, shaping the evolution of our scientific data ecosystems and AI-enabled discovery workflows.

Qualifications

• Ph.D. or MS in Computer Science, Bioinformatics, or related STEM field.
• 8+ years (Ph.D.) or 12+ years (MS) experience in scientific data architecture, platform development, or informatics.
• Deep expertise in data modeling, semantic technologies (RDF, OWL, SPARQL), knowledge graphs, and cloud data platforms.
• Experience in large-scale scientific data systems and AI-ready data ecosystems.

Responsibilities

• Define strategy and standards for data modeling, metadata management, ontologies, semantic interoperability, and knowledge graphs.
• Lead architecture design and implementation; mentor and oversee a team of data architects.
• Promote best practices and architecture adoption; shape evolution of scientific data ecosystems.

Skills

Data modeling

Semantic technologies

Knowledge graphs

Cloud data platforms

Databricks

Snowflake

Education

Ph.D. in Computer Science or related STEM

MS in Computer Science or related STEM

Tools

RDF

OWL

SPARQL

Job description

Role

Senior Director, Data Architecture within Lilly's Data Foundry team, leading scientific information architecture to accelerate AI-native drug discovery in Molecular Discovery.

Responsibilities

• define strategy and standards for data modeling, metadata management, ontologies, semantic interoperability, and knowledge graphs; lead architecture design and implementation; mentor and oversee a team of data architects; promote best practices and architecture adoption; shape the evolution of scientific data ecosystems.

Requirements

• Ph.D. or MS in Computer Science, Bioinformatics, or related STEM field; 8+ years (Ph.D.) or 12+ years (MS) experience in scientific data architecture, platform development, or informatics; deep expertise in data modeling, semantic technologies (RDF, OWL, SPARQL), knowledge graphs, and cloud data platforms (e.g., Databricks, Snowflake); experience in large-scale scientific data systems and AI-ready data ecosystems.

Preferred

• experience leading technical teams, familiarity with discovery workflows (chemistry, biology, genomics), and knowledge of laboratory informatics platforms.

High-Value

• scientific informatics, knowledge graphs, FAIR data, semantic architectures, cloud-native platforms, AI/ML enablement, and discovery science workflows.

WorkSetup

• remote with leadership and collaboration responsibilities.