# Harnham — Director, Enterprise Data

- Generated: 2026-09-02 09:34:05 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4462081693/
- Provider: linkedin
- Posting time: approximately 2026-09-01 08:34 PM EDT (estimated from provider's '13 hours ago' at capture)
- Applicants: 32 applicants
- Work model/location: Fully remote; Massachusetts is eligible.; provider location: United States
- Compensation: Approximately $265K target, maximum $300K, plus 20% bonus; qualifies.
- Travel: Occasional travel to Dallas; percentage not disclosed.
- Positioning track: Executive Leader
- Fit outcome: FAIL — 83.3%

## Direct-match strengths

Data modernization, AWS cloud, pipelines, governance, analytics, APIs, Kafka, and AI-ready architecture.

## Hard or material gaps

Required 60-person multi-layer organization is materially beyond Keith's demonstrated 24-25-person operating scope; current outcome-backed Snowflake/lakehouse evidence is weak.

## Evidence map

1. Enterprise data-platform strategy (w3/e3): Defined and delivered TriMark's enterprise AWS data lake.
2. Large data organization (w3/e2): Led 24-25-person teams and managers, below the inherited 60-person scope.
3. Warehouse/lakehouse/Snowflake (w3/e2): Deep data-lake evidence and Snowflake listed, but no recent Snowflake outcome.
4. Streaming/real-time/Kafka (w2/e2): Kafka/MSK and event-driven architecture with limited quantified real-time outcomes.
5. ETL/ELT/pipelines/APIs (w3/e3): TriMark pipelines plus extensive API and cloud-platform delivery.
6. Governance/metadata/quality (w2/e3): MassMutual governance/catalog work and TriMark normalization.
7. Scale/reliability/cost/observability (w3/e2): Strong cloud operations, less direct at a 60-person data-platform scale.
8. Large-scale BI/analytics (w2/e3): $1B company, 11 ERPs, 50+ KPIs, and 60x faster reporting.
9. AI-ready data (w2/e3): AssistX, RAG, PGVector, and enterprise AI/data architecture.
10. Consumer-facing real-time products (w1/e2): Customer-facing SaaS/cloud systems, not a direct large consumer-data platform.

## Full normalized job description

Director, Enterprise Data
Location:
Fully Remote, with occasional travel to Dallas, TX
Restricted States:
Candidates cannot work from California, New York, Hawaii, North Dakota, Oregon, Rhode Island, Washington, or Wyoming
Work Authorization:
U.S. Citizen or Green Card Holder
Base Salary:
Target of approximately $265,000, with a maximum of $300,000
Bonus:
20% annual bonus
Benefits:
Healthcare, 401(k), and comprehensive benefits
The Opportunity
A large, multi-billion-dollar organization is looking for a Director of Enterprise Data to lead a large-scale Data Engineering and Analytics Engineering organization through its next stage of modernization.
The organization is investing heavily in its data and AI capabilities, moving beyond traditional static BI dashboards toward real-time, conversational, and AI-enabled data experiences across internal and customer-facing digital products.
This leader will inherit an established organization of approximately 60 people across permanent and contract resources and will be responsible for the enterprise data platforms, engineering capabilities, and architecture that support analytics, AI, machine learning, and digital products at scale.
What You’ll Do
Define and execute the enterprise data platform strategy and roadmap.
Lead large Data Engineering and Analytics Engineering teams responsible for enterprise-scale data platforms.
Oversee lakehouse and warehouse architecture, data pipelines, APIs, streaming, ingestion, and real-time integration.
Drive the continued modernization of the organization’s cloud-native data ecosystem.
Own the scalability, reliability, latency, observability, and cost optimization of enterprise data platforms.
Establish standards across data modeling, ingestion, metadata, lineage, data quality, and platform operations.
Partner closely with Data Science, AI Engineering, Governance, Product, and other technical leaders to build trusted, scalable, AI-ready data products.
Help evolve traditional BI and analytics capabilities toward real-time, conversational, GenAI, and agentic AI-enabled experiences.
Lead and develop a large, distributed organization across permanent employees and contract resources.
What We’re Looking For
12+ years of technology experience with significant leadership experience across Data Engineering, Analytics Engineering, Enterprise Data, or Business Intelligence.
Proven experience leading large data organizations, ideally 25–30+ people through a combination of direct and indirect reports.
Strong experience leading Data Engineering and/or Analytics Engineering functions rather than traditional Software Engineering organizations.
Deep experience with modern enterprise data platforms, data warehouses, and lakehouse architectures.
Strong, current experience with
Snowflake
.
Experience with cloud-native data platforms and modern data architecture.
Strong understanding of
streaming and real-time data processing
, with technologies such as Kafka or similar platforms.
Experience with modern
ETL/ELT
architectures and data pipelines.
Experience delivering and supporting
APIs
as part of enterprise data platforms and products.
Experience with data quality, governance, metadata, lineage, reliability, observability, and platform operations.
Experience supporting large-scale BI, analytics, and business intelligence environments.
Experience operating enterprise data platforms with a focus on scalability, reliability, performance, and cost optimization.
AI & Modern Data Experience
You do not need to be a dedicated AI or Generative AI expert.
However, this organization is making a significant investment in AI-enabled products and wants a data leader who understands where modern data platforms are heading.
Experience supporting
AI/ML, Generative AI, agentic AI, conversational analytics, or other AI-driven products
is highly valuable. The ideal candidate understands how enterprise data engineering must evolve to support real-time and AI-driven consumption rather than relying exclusively on traditional dashboards and reporting.
Ideal Background
Candidates may come from healthcare, but healthcare experience is not required.
Strong backgrounds could also come from:
Retail
Banking or financial services
Digital businesses
Large-scale customer-facing organizations
Other complex or regulated enterprise environments
Experience supporting
consumer-facing, real-time data products
is particularly relevant.
Leadership Scope
This role will lead an organization of approximately
60 people
, consisting of roughly
60% permanent employees and 40% contract resources
.
The successful candidate does not need to have had 60 direct reports. However, they should have demonstrated experience leading a substantial organization through multiple layers of leadership and managing both employees and external resources.
Preferred Experience
Enterprise-scale data modernization
Distributed Data Engineering organizations
dbt or similar modern analytics engineering technologies
AI/ML, GenAI, or agentic AI workloads
Real-time or streaming data architectures
Consumer-facing digital products
Healthcare or another regulated industry
Ontology or knowledge graph concepts

## Artifact metadata

- Resume and cover letter: Not generated under the fit gate.
- Archived JD capture: https://files.keithsteward.com/Harnham_Enterprise_Data/Keith_Steward_director-enterprise-data_4462081693_JD_capture.md
- Google Drive used: No