Advisor – Data Architect, Data Foundry

Eli Lilly and Company

Data Architect designing and building data infrastructure for AI-native drug discovery at Lilly. Collaborating across multiple focus areas including data modeling and lakehouse architecture.

Posted 6/5/2026full-timeSan Francisco • California, Colorado, Massachusetts • 🇺🇸 United StatesMid-LevelSenior💰 $151,500 - $244,200 per yearWebsite

Tech Stack

Tools & technologies

ETLKafkaMongoDBNeo4jSpark

About the role

Key responsibilities & impact

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.
Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent).
Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools.
Implement real-time and streaming data integration (Kafka, Kinesis) connecting LIMS, instruments, and lab automation systems to the data infrastructure.
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.

Requirements

What you’ll need

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)

Benefits

Comp & perks

Eligibility to participate in a company-sponsored 401(k)
Pension
Vacation benefits
Eligibility for medical, dental, vision and prescription drug benefits
Flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
Life insurance and death benefits
Certain time off and leave of absence benefits
Well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data modelingontology engineeringETLELTdata lakehouse architecturesemantic data standardsknowledge graphsstreaming data integrationcontrolled vocabulariesmetadata standards