Job description

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. Agentic AI & Intelligent Workflows • 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. Business Enablement & Reporting • 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. Leadership & AI Thought Leadership (Phased) • 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. Quality, Governance & Compliance • 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. The use of external recruiters/staffing agencies requires prior approval from our Human Resources Department. The Human Resources Department at Imperative Care requests that external recruiters/staffing agencies not to contact Imperative Care employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with Imperative Care. Imperative Care will not accept unsolicited resumes from any source other than candidates themselves for either current or future positions. Submission of unsolicited resumes in advance of an agreement between the Human Resources Department and the external recruiter/staffing agency does not create any implied obligation on the part of Imperative Care.

Requirements

Must-haves

Title: Sr Data Engineering Manager
Why Imperative Care?
Do you want to make a real impact on patients?
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.
Agentic AI & Intelligent Workflows • 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.
Business Enablement & Reporting • 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.
Leadership & AI Thought Leadership (Phased) • 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.
Quality, Governance & Compliance • Ensure solutions meet compliance and security expectations and are designed for scalability from the outset.
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.
Effective communicator across technical and business audiences.
Join Us! Imperative Care

Nice-to-haves

Master’s degree preferred.
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.

Application prep

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Keywords to mirror

aiml

Platform: jazzhr
Effort: medium

Benefits

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401k

Pto

Parental Leave