Advisor - Data Architect, Data Foundry

Initial Therapeutics, Inc.; San Francisco (CA); On-site; USD 151,500 - 222,200; Full time

Benefits offered by this job

401(k) participation

Medical, dental, and vision benefits

Flexible spending accounts

Job summary

Initial Therapeutics, Inc. is seeking Data Architects in San Francisco, CA, to design data infrastructures for AI-native drug discovery. The role requires expertise in relational databases, data modeling, and knowledge graph design. Candidates should possess an M.S. or PhD, with strong experience in ETL/ELT pipelines and modern data platforms such as Databricks or Snowflake. The compensation range is anticipated between $151,500 and $222,200, with comprehensive company benefits including retirement plans, healthcare, and more.

Qualifications

• M.S. or PhD in relevant STEM field required.
• Experience in data architecture or scientific informatics crucial.
• Deep expertise in data modeling or database systems essential.

Responsibilities

• Design and implement data models and schemas.
• Build ETL/ELT pipelines for scientific data.
• Architect knowledge graphs and specialized data systems.

Skills

Data modeling

Relational databases

Data platform architecture

Knowledge graph design

ETL/ELT skills

Education

M.S. or PhD in Computer Science or related field

Tools

Databricks

Snowflake

Spark

Neo4j

MongoDB

Job description

Location

San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN

Reports to

Lead, Data Architecture (R9), Architecture4Insight

Company Overview

Lilly is a global healthcare leader headquartered in Indianapolis, Indiana, focused on discovering and delivering life‑changing medicines.

Data Foundry

The Data Foundry is a multidisciplinary team within Discovery Technology and Platforms (DTP) enabling AI‑native drug discovery through four pillars: Architecture4Insight, Methods4Insight, Automation & Scale4Insight, and Preparedness4Insight.

Position Summary

We are seeking Data Architects at multiple levels to design and build the data infrastructure that enables AI‑native drug discovery. The role builds schemas, ontologies, data models, knowledge graphs, and platform architectures for scientific data.

Responsibilities

Data Modeling & Ontologies

• Design and implement data models, schemas, and ontologies for chemical, biological, and automation‑generated data that serve discovery workflows across the portfolio.
• Define and maintain controlled vocabularies, metadata standards, and FAIR‑compliant data frameworks in partnership with Preparedness4Insight.
• Implement semantic data standards (RDF, OWL, SPARQL) and ontology engineering practices to create interoperable, machine‑readable scientific data.

Data Platform & Lakehouse Architecture

• Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent), including data storage patterns, partitioning strategies, and query optimization.
• Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools to transform raw scientific data into analytical and ML‑ready formats.
• Implement real‑time and streaming data integration (Kafka, Kinesis, event‑driven patterns) connecting LIMS, instruments, and lab automation systems to the data infrastructure.

Knowledge Graph & Specialized Data Systems

• Design and implement knowledge graphs (Neo4j, Amazon Neptune, TigerGraph) that capture molecular, target, pathway, and experimental relationships across the discovery landscape.
• Architect specialized data solutions: array databases (TileDB) for genomics/imaging, document stores (MongoDB) for experimental records, and vector databases for embedding‑based retrieval supporting ML and RAG workflows.
• Build query and traversal patterns that enable scientists and AI agents to ask relational questions across the entire data landscape.

Cross‑Functional Partnership

• Partner with scientific software engineers to ensure data architectures are implementable, performant, and well‑documented.
• Collaborate with Methods4Insight to design data structures that support analytical model training, deployment, and evaluation.
• Work with Tech@Lilly to define scaling strategies, ensure enterprise compliance, and transition data architectures to production‑grade management.
• Contribute to build‑versus‑buy‑versus‑adopt decisions by evaluating commercial and open‑source data platforms against Data Foundry requirements.

Basic Requirements

• M.S. or PhD in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field
• MS (with 6+ years) and PhD (with 2+ years) of data architecture, data engineering, or scientific informatics experience.
• Deep expertise in at least one of the focus areas: relational databases, data modeling and ontology engineering, data platform and lakehouse architecture (Databricks, Snowflake, Spark), or knowledge graph and specialized database systems (Neo4j, Neptune, MongoDB, TileDB).

Preferred Qualifications

• Working familiarity with multiple database paradigms — relational, graph, document, columnar, key‑value — and strong SQL skills.
• Understanding of scientific data types and experimental workflows in life sciences or pharma (chemical, biological, HTE data).
• Strong communication skills with ability to translate data architecture concepts for both technical and scientific audiences.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data integration patterns.
• Pharmaceutical or biotech research industry experience, particularly in discovery data management or research informatics.
• Experience with semantic web technologies: RDF, OWL, SPARQL, Protégé, or equivalent ontology engineering tools.
• Hands‑on experience with graph databases (Neo4j, Neptune, TigerGraph) and knowledge graph design patterns for scientific data.
• Data lakehouse architecture experience: Databricks (Delta Lake, Unity Catalog), Snowflake, or equivalent; ETL/ELT with Spark, dbt.
• Experience with streaming/real‑time data platforms (Kafka, Kinesis, Flink) and event‑driven architectures.
• Familiarity with LIMS, ELN systems (e.g., Benchling), and laboratory instrument data integration.
• Experience with vector databases (Pinecone, Weaviate, pgvector) and embedding‑based retrieval for ML/RAG applications.
• Array database experience (TileDB, Zarr) for genomics, imaging, or high‑dimensional scientific data.
• FAIR data principles implementation experience and Data Readiness Level frameworks.
• Scientific data standards and controlled vocabularies in chemistry (InChI, SMILES) or biology (Gene Ontology, UniProt).
• Experience with C, C++, or Rust for performance‑critical data processing; familiarity with HPC data I/O patterns for large‑scale scientific computations.

Compensation and Benefits

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position ranges from $151,500 to $222,200. Full‑time equivalent employees will be eligible for a company bonus (depending, in part, on company and individual performance). Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company‑sponsored 401(k); pension; vacation benefits; medical, dental, vision, and prescription drug benefits; flexible benefits (healthcare and/or dependent day‑care flexible spending accounts); life insurance and death benefits; time‑off and leave of absence benefits; and well‑being benefits (employee assistance program, fitness benefits, and employee clubs and activities). Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

EEO Statement

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce. If you require accommodation, please complete the accommodation request form for further assistance.