Data Architect, Next Platform
Remote · USFull-time$140–190K/yrPosted 1mo agoStill listed 2w ago
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Job overview
Tempus Labs is hiring a Data Architect, Next Platform. Tempus seeks a Data Architect to design a high‑scale, multi‑modal healthcare data ecosystem, integrating structured EHR records, genomics, and imaging data for AI‑driven clinical insights, while ensuring HIPAA compliance, data quality, and multi‑tenant performance across hybrid cloud environments.
Key focus areas include Lead design and management of enterprise data model integrating clinical, genomics, and imaging domains, Architect scalable data solutions for federated hospital networks ensuring multi‑tenancy and high availability, and Design data access patterns and metadata layers optimized for autonomous AI agents.
Successful candidates bring Bachelor’s Degree In Computer Science, Health Informatics, Or A Related Field, 7+ Years Data Architecture Experience, and Significant Healthcare Or Life Sciences Domain Experience. Important skills include Multi-Modal Architecture Design, Data Solution Architecture, Data Access Pattern Design, Metadata Layer Optimization, Entity-Relationship Diagrams, and Data Dictionaries. Preferred (not required): AI Data Engineering, Pinecone, Weaviate, and pgvector.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
We are seeking a Data Architect to design the structural backbone of a high-scale, multi-modal healthcare data ecosystem. You will be responsible for architecting data environments that serve massive networks of hospitals, ensuring that diverse data types—ranging from structured EHR records to unstructured genomic and imaging data—are seamlessly accessible to autonomous AI agents.
Our goal is to move beyond static data warehousing to create a dynamic, "agent-ready" data fabric that supports real-time clinical evaluation at an enterprise scale.
What You’ll Do
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Multi-Modal Architecture: Lead the design and management of an enterprise data model that integrates complex domains including clinical EHR records, high-throughput genomics (NGS), and cardiovascular imaging (Echo, Cath, ECG).
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Scale for Hospital Networks: Architect data solutions designed to scale across federated networks of hospitals, ensuring multi-tenancy, high availability, and performance across hybrid cloud environments.
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Enable Agentic Workflows: Design data access patterns and metadata layers specifically optimized for AI agents, allowing them to autonomously discover, query, and reason over structured and unstructured datasets.
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Schema & API Ownership: Author and maintain entity-relationship diagrams (ERDs), data dictionaries, and API specifications across multiple technologies (Relational, NoSQL, Vector Databases).
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Data Quality & Traceability: Implement automated solutions to monitor data quality and lineage with strict traceability back to source systems, ensuring "ground truth" for agentic evaluations.
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Technical Advocacy: Educate engineering and clinical teams on data modeling standards, governance, and best practices for maintaining data integrity in a HIPAA-regulated environment.
Experience & Qualifications
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Education: Bachelor’s Degree in Computer Science, Health Informatics, or a related field.
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Professional Experience: 7+ years in data architecture or enterprise modeling, with significant experience in the healthcare or life sciences domain.
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Modeling Mastery: Expert-level knowledge of 3NF, Dimensional (Star Schema), and Data Vault 2.0 modeling techniques.
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Advanced SQL & Python: Exceptional SQL skills for complex analytical environments and proficiency in Python for data profiling and debugging.
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Technology Strategy: Ability to articulate the trade-offs between RDBMS, MPP, and NoSQL technologies, and experience implementing Master Data Management (MDM) solutions.
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Interoperability Standards: Deep familiarity with HL7, FHIR, and Epic/Cerner data structures.
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Tools: Proficiency with modeling tools such as Erwin, Vertabelo, or Lucidchart.
Bonus Points
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AI Data Engineering: Experience with Vector databases (e.g., Pinecone, Weaviate, or pgvector) or Graph databases to support RAG and agentic memory.
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Cloud Architecture: Hands-on experience with GCP (BigQuery, Vertex AI) or AWS healthcare-native services.
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Specialized Clinical Data: Direct experience working with EHR, OMOP, DICOM, genomic data models, or longitudinal patient records.
#LI-BL1
Chi: $140,000-$190,000 NYC/SF: $150,000-$200,000
The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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