# Harnham — Director, Enterprise Data

- Generated: 2026-09-01 09:47:33 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4461509752/
- User-provided LinkedIn posting: https://www.linkedin.com/jobs/view/4461509752/
- Posting time: approximately 2026-08-31 08:47 PM EDT (estimated from LinkedIn's '13 hours ago' at capture)
- Applicants: 26 applicants
- Work model/location: Remote — United States; LinkedIn location: United States
- Compensation: $245,000-$300,000 base plus bonus
- Travel: Not disclosed
- Positioning track: Executive leader
- Fit outcome: FAIL — 58%

## Direct-match strengths

Enterprise data strategy, cloud data platforms, AI-ready data products, APIs, streaming, governance, observability, metadata, knowledge graphs, healthcare technology, and executive leadership.

## Hard or material gaps

Hard scale, technology-depth, and education gaps: the JD requires proven management of 40-60+ engineers, deep current hands-on Snowflake leadership, and a CS/engineering/information-systems degree. Keith's largest documented engineering organization is approximately 25; Snowflake is supported but not at the required depth; his degrees are biological sciences.

## Evidence map

1. Enterprise data-platform strategy (weight 3, evidence score 3/3) — Direct TriMark, AWS, MassMutual, and NorthBay evidence.
2. Lakehouse, streaming, APIs, and cloud pipelines (weight 3, evidence score 2/3) — Direct data-lake, Spark, Kafka, API, and cloud evidence; lakehouse depth is less explicit.
3. Manage 40-60+ engineers (weight 3, evidence score 1/3) — Teams up to 25 plus larger influence communities, below the direct-management requirement.
4. Deep current Snowflake leadership (weight 3, evidence score 1/3) — Snowflake is source-supported, but deep current operating leadership is not.
5. ELT ownership, modeling, lineage, observability, cost (weight 3, evidence score 2/3) — Strong adjacent/direct platform evidence, but not every named discipline at the requested scale.
6. AI/GenAI-ready data products (weight 2, evidence score 3/3) — Direct production AI and data-platform evidence.
7. Healthcare or regulated-industry context (weight 2, evidence score 3/3) — Direct health, pharma, FDA, HIPAA, and financial-services experience.
8. Required degree discipline (weight 3, evidence score 0/3) — Ph.D. and B.Sc. are in molecular biology/microbiology and immunology.

## Full normalized job description

Director, Enterprise Data
Location:
Remote
Compensation:
$245,000–$300,000 Base + Bonus
About the Role
We are searching for a
Director, Enterprise Data
to lead the data platform strategy for one of the nation’s largest non-profit healthcare systems. Operating with over $17B in annual revenue and serving millions of patients across Texas, the organization is making massive investments in AI, agentic AI, and real-time consumer digital experiences.
In this role, you will report directly to the Senior Vice President and lead an established team of ~60 engineers (a mix of permanent staff and key contractor resources). Your core focus will be raising the technical bar and shifting the organization from traditional, static BI/dashboards to real-time, AI/chat-enabled data consumption models.
Key Responsibilities
Platform Strategy & Architecture:
Define and execute the enterprise data platform strategy, driving modern lakehouse architectures, real-time streaming, and API integrations.
Engineering Leadership:
Lead, mentor, and scale a 60-person engineering organization (perm + contract workforce) focused on cloud-native data pipelines and platform operations.
AI & Product Enabling:
Partner cross-functionally with peer Directors across AI Engineering, Ontology & Knowledge Products, and Governance to deliver AI-ready data products for internal teams and consumer-facing applications.
Platform Optimization:
Maintain end-to-end ownership over platform scalability, latency, observability, metadata, lineage, and cost optimization.
Technical Standards:
Establish best-in-class standards for modern ELT code, data modeling, ingestion, and governance across cloud environments.
Qualifications & Requirements
Must-Haves:
Snowflake Expertise:
Deep, current, and direct hands-on leadership experience within Snowflake environments.
Leadership Scale:
12–18+ years of overall technology experience, including 7+ years leading data engineering teams. Proven experience managing large-scale teams (40–60+ engineers) across a blended perm/contract workforce.
Engineering Discipline:
Deep experience managing teams that own their own ELT code and build scalable streaming, API, and cloud data platform infrastructure.
Education:
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
Preferred Qualifications:
AI/GenAI Exposure:
Direct experience building toward or supporting AI, ML, GenAI, or agentic AI data workloads.
Industry Experience:
Healthcare background is strongly preferred. High-volume, highly regulated industries (e.g., Banking, Retail) with enterprise consumer data scale are also welcome.
Modern Concepts:
Familiarity with ontology, knowledge graphs, or advanced metadata lineage standards.

## Artifact metadata

- Resume and cover letter: Not generated under the fit gate.
- Archived JD capture: https://files.keithsteward.com/Harnham/Keith_Steward_Director_Enterprise_Data_4461509752_JD_capture.md
- Google Drive used: No