The Role
Architect and build Imperative Care’s modern semantic data platform, knowledge graph, and enterprise AI foundation. Develop production generative AI agents, RAG solutions, intelligent workflows, and system integrations. Establish data governance, security, lineage, quality, and stewardship controls for a regulated environment. Enable self-service analytics and reporting while partnering with business, technology, vendors, and managed-service providers. Serve as an AI thought leader, drive adoption, and contribute to hiring and mentoring as capabilities expand.
Summary Generated by Built In
Title: Sr Data Engineering Manager
This position is based in our Campbell, California offices. This position is on-site, full-time.
Why Imperative Care?
Do you want to make a real impact on patients?
As part of our team at Imperative Care, you can help elevate care for patients suffering from stroke and other devastating vascular diseases. Every day, the technologies that we develop at Imperative Care directly impact people at the most vulnerable moments of their lives. Our focus is on the needs of the patient, and they come first in everything we do.
What You’ll Do
The Sr. Data Engineering Manager serves as the subject matter expert in this field to build and lead the foundation of Imperative Care’s modern data architecture and AI capability. This includes technology such as Modern Data Platform, Enterprise AI, Agentic AI, and Semantic Data Architecture. This role is an individual contributor responsible for leading and establishing Imperative Care's semantic data warehouse and enterprise knowledge graph strategy (AI-ready enterprise data foundation) and through collaboration efforts, spearhead the development of practical agentic AI capabilities across Imperative Care’s core business areas and systems. This position designs and owns a modern, semantic data platform that unifies the company’s core business systems and unstructured content into a governed, connected data layer, and serves as the organization’s hands-on builder and corporate leader for agentic AI. This role will architect, build, pilot, and deploy a unified data platform and drive AI agents’ orchestration directly across core business systems, enabling governed analytics, business enabled self-service reporting, retrieval-augmented generation (RAG), AI agents development, and workflow automation.
Modern Data Platform & Architecture
- Design and own a modern, semantic data platform that connects key business systems—ERP, CRM, marketing technologies, contract/legal management software, purchasing, quality management, and business intelligence (e.g., tools such as QAD, Salesforce, HubSpot, Agiloft, Coupa, Propel, and Tableau)—together with unstructured and flat-file content, into a unified and governed data layer.
- Evaluate and select the target architecture, weighing a semantic / knowledge-graph approach that connects data largely in place against a medallion / star-schema warehouse, and define the roadmap, build-vs-virtualize decisions, and total cost of ownership.
- Build and maintain the knowledge graph and semantic layer using modern graph, semantic, and data-integration tooling (e.g., tools such as knowledge-graph platforms and data-sync / virtualization tools), enabling bi-directional sync, data cleansing, and master / reference data alignment.
- Implement enterprise data security and governance using role- and attribute-based access control (RBAC / ABAC), along with data lineage, quality, and stewardship controls appropriate to a regulated environment.
- Serve initially as the hands-on builder—designing, prototyping, and deploying production AI agents and intelligent workflows that connect systems to actions and insights.
- Build agent capabilities including tool / function calling, context and memory management, multi-agent orchestration, retrieval-augmented generation (RAG), and human-in-the-loop checkpoints.
- Implement prompt-engineering and reasoning strategies, validate value through measurable outcomes, and iterate rapidly from pilot to production.
- Partner with managed-service providers (MSPs) and vendors to scale agent development and workflow automation across business processes.
- Empower business teams to self-serve analytics by providing the foundation of data, standards, and support that distributed report developers need.
- Enable the business to build their own report and support data governance efforts. Where needed, lead the buildout of selected high-value reports directly.
- Collaborate with data and analytics teams to improve data reporting, forecasting, and decision-support capabilities.
- Act as an AI thought leader and change agent—driving adoption, educating stakeholders, and promoting a culture of experimentation and data-driven decision-making.
- Translate fluently between technical and non-technical audiences and drive alignment across IT, Finance, Sales, Marketing, Legal, and Quality.
- Contribute to hiring, onboarding, and mentoring as the capability scales.
- Ensure solutions meet compliance and security expectations and are designed for scalability from the outset.
What You’ll Bring:
- Bachelor’s degree in computer science, software engineering, data engineering, or a related discipline and a minimum of 12 years of experience in data engineering / architecture, applied AI / ML, or enterprise application development; or an equivalent combination of education and related experience.
- Master’s degree preferred.
- Demonstrated experience architecting modern data platforms—semantic layer and knowledge graph, and / or medallion / lakehouse—and integrating heterogeneous enterprise source systems and unstructured content.
- Experience should include a minimum of 2 years of progressive recent, hands-on experience building production generative-AI and agentic solutions (LLMs, agent frameworks, RAG, orchestration, tool / function calling).
- Knowledge of data governance and security models, including RBAC / ABAC, and of bi-directional data sync and data-cleansing patterns.
- Proven ability to deliver pilots and proofs-of-concept end-to-end and scale them into production.
- Experience in or alongside regulated environments—GxP, 21 CFR Part 11, computer system validation (CSV / CSA), GAMP 5, and HIPAA—strongly preferred.
- Cloud infrastructure hands-on knowledge; experience managing vendors / MSPs (SOWs, licensing, budgets) preferred.
- Effective communicator across technical and business audiences.
Employee Benefits include a stake in our collective success with stock options, competitive salaries, a 401k plan, health benefits, generous PTO, and a parental leave program.
Join Us! Imperative Care
Salary Range: $220,000 – 245,000 annually
Please note that the salary information is a general guideline only. Imperative Care considers factors such as scope and responsibilities of the position, candidate's work experience, education/training, key skills, and internal equity, as well as location, market and business considerations when extending an offer. As part of our total rewards package, Imperative Care offers comprehensive benefits including a 401k plan, health benefits, generous PTO, a parental leave program and emotional health resources.
Skills Required
- Bachelor’s degree in computer science, software engineering, data engineering, or a related discipline, or equivalent education and experience.
- Minimum 12 years of experience in data engineering, data architecture, applied AI/ML, or enterprise application development.
- Experience architecting modern data platforms, including semantic layers, knowledge graphs, medallion architectures, or lakehouses.
- Experience integrating heterogeneous enterprise source systems and unstructured content.
- At least 2 years of recent, hands-on experience building production generative AI and agentic AI solutions.
- Experience with LLMs, agent frameworks, RAG, orchestration, and tool or function calling.
- Knowledge of data governance and security models, including RBAC and ABAC, plus bidirectional data synchronization and data cleansing.
- Proven ability to deliver pilots and proofs of concept end-to-end and scale them into production.
- Effective communication across technical and business audiences.
- Master’s degree.
- Experience in or alongside regulated environments involving GxP, 21 CFR Part 11, CSV/CSA, GAMP 5, or HIPAA.
- Hands-on cloud infrastructure knowledge.
- Experience managing vendors or managed-service providers, including SOWs, licensing, and budgets.
Imperative Care Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Imperative Care and has not been reviewed or approved by Imperative Care.
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Fair & Transparent Compensation — Posted salary bands for multiple roles are explicit and compare favorably to U.S. norms in several functions. Publicly listed ranges help anchor expectations and indicate a market‑competitive stance.
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Equity Value & Accessibility — Stock options are consistently included as part of offers and total rewards. Equity is positioned as a meaningful component alongside base pay and, in some roles, bonus.
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Leave & Time Off Breadth — Company materials highlight generous PTO and a parental leave program as standard benefits. Multiple postings reiterate these time‑off elements across roles.
Imperative Care Insights
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The Company
What We Do
Imperative Care is a Silicon Valley-based medical technology company focused on developing the next generation of innovative solutions to address the vast and urgent needs in stroke intervention and peripheral thrombectomy. With a physician-driven approach and a culture of rapid innovation, we are working to improve every aspect of the stroke procedure with the goal of bringing patients the best care possible. We have two 510(k) cleared product platforms, as well as an expansive technology development pipeline. Follow us for updates as we work to change the way stroke is treated. For important safety and risk information, visit bit.ly/3yWkfEJ.
