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Data Foundry Jobs (NOW HIRING)

Palantir Lead -Onsite Role

Los Angeles, CA · On-site

$110K - $145K/yr

Expertise in Palantir Data Foundry, Ontology and Python knowledge. * Must have experience with code repository and utility driven development * Proficient with Transform API within Foundry

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Palantir Foundry

Reading, PA · On-site

$16.50 - $21.25/hr

Job Title: Palantir Foundry Work Location: Reading, PA Duration: Long Term Mandatory Skills ... Data Transformation (Code Repository & Pipeline Builder), analysis (Contour and Quiver ...

Design and develop Foundry-native data pipelines across ingestion, transformation, ontology modeling, and dataset materialization layers. * Build and maintain modular pipeline components (Code Repos ...

Design and develop Foundry-native data pipelines across ingestion, transformation, ontology modeling, and dataset materialization layers. * Build and maintain modular pipeline components (Code Repos ...

A structural data advantage. Direct access to one of the largest independent e-commerce fulfillment networks in the U.S.-an operational environment that would be extremely difficult for a startup to ...

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Data Foundry information

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How much do data foundry jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for data foundry in the United States is $27.71, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $34.62 per hour, depending on experience, location, and employer.

What is a data foundry?

A Data Foundry is an organization or platform that provides secure data storage, management, and processing services, often for enterprises or research institutions. These facilities offer robust infrastructure, including data centers, networking, and cloud services, to support large-scale data operations. Data Foundries help organizations manage data lifecycle needs, ensure data security, and enable efficient data sharing and analysis. They play a critical role in supporting digital transformation and big data initiatives.

How does a data foundry professional typically collaborate with data engineers and analysts within an organization?

A Data Foundry professional plays a central role in facilitating smooth data operations by acting as a bridge between data engineers, who build and maintain data infrastructure, and data analysts, who interpret and use data for decision-making. They often coordinate data ingestion, ensure data quality, and manage data pipelines so that analysts can access accurate and timely information. Regular cross-functional meetings, documentation, and use of collaborative tools are common practices to align goals and resolve any data-related challenges. This teamwork ensures that data flows seamlessly from its source to actionable insights.

What are the key skills and qualifications needed to thrive as a data engineer at a data foundry, and why are they important?

To thrive as a Data Engineer at a data foundry, you need a strong background in computer science, data modeling, and database management, often supported by a relevant degree or certification. Proficiency in tools and systems such as SQL, Python, ETL frameworks, big data platforms (Hadoop, Spark), and cloud services (AWS, Azure) is crucial. Strong problem-solving skills, attention to detail, and effective communication distinguish top performers in this role. These competencies enable the reliable extraction, transformation, and delivery of high-quality data that powers organizational analytics and decision-making.

What is the difference between Data Foundry vs Data Engineer?

AspectData FoundryData Engineer
CredentialsTypically requires data management certifications, database knowledge, and sometimes cloud platform certificationsRequires similar credentials such as SQL, Python, cloud certifications, and data modeling expertise
Work EnvironmentOften involves working with data infrastructure, data pipelines, and cloud platforms in data-centric organizationsWorks on designing, building, and maintaining data pipelines and architectures in various industries
Industry UsageCommonly used in data management, cloud services, and data infrastructure companiesWidely used across tech, finance, healthcare, and other data-driven sectors

Data Foundry and Data Engineer roles share overlapping skills in data management and cloud platforms. While Data Foundry often emphasizes data infrastructure setup and cloud data services, Data Engineers focus on building and maintaining data pipelines and architectures. Both roles are essential in data-driven organizations, with similar credentials and work environments, making them closely related but distinct in their specific focus areas.

More about Data Foundry jobs

What cities are hiring for Data Foundry jobs?

Cities with the most Data Foundry job openings:

What states have the most Data Foundry jobs?

States with the most job openings for Data Foundry jobs include:

Infographic showing various Data Foundry job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $57,633 per year, or $27.7 per hour.

Advisor - Data Architect, Data Foundry

San Francisco, CA • On-site

Initial Therapeutics, Inc.
Biotechnology Research and Development • 11 - 50 employees

$151.50 - $222.20/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


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.

ResponsibilitiesData 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.

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