OA – Enterprise Data Architect - 26-10352

Compu-Vision - IT; York (York County); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Compu-Vision - IT is seeking an Enterprise Data Architect in a hybrid role based in Harrisburg, PA. The position focuses on defining enterprise information architecture, data models, and reusable data products to support modernization, analytics, and AI initiatives.

You will partner with business leaders and engineering teams to drive data governance, security, and cross-domain data sharing, while guiding data platforms across Snowflake, Databricks, and cloud ecosystems.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, or a related field.
• Minimum 10 years of experience in data architecture, information architecture, or enterprise architecture.
• 8+ years in data architecture, data engineering, or advanced database design and modeling.
• Experience designing or implementing data warehouses and data marts.

Responsibilities

• Define conceptual and logical data models for common business entities and establish canonical data models.
• Partner with modernization teams to incorporate reusable data products into solution designs.
• Identify and support the design of reusable data products and establish data quality requirements.
• Establish data governance principles, standards, metadata, and lineage practices.
• Collaborate with cloud, integration, and data teams to implement enterprise data products.

Tools

Snowflake

Databricks

MongoDB

AWS

Azure

GCP

Job description

OA – Enterprise Data Architect

Duration: Contract Location: Harrisburg, PA 17120 — Hybrid, with one day per week onsite (Tuesday, Wednesday, or Thursday)

Overview

The Enterprise Data Architect is responsible for defining and evolving enterprise information architecture and reusable data products to support modernization, analytics, and AI initiatives. This role partners with business leaders, product and engineering teams, and enterprise technology organizations to identify information assets that should be shared across domains and those that should remain domain-specific. The position will define data domains, develop data models, establish data quality standards, map source systems to enterprise domains, and support data contracts for modernization initiatives and future AI capabilities. The ideal candidate will have a strong understanding of data architecture principles, practical data modeling experience, and expertise in data-centric enterprise architecture.

Key Responsibilities

1. Enterprise Information Architecture

• Define conceptual and logical data models for common business entities.
• Establish canonical data models and enterprise information standards.
• Define relationships between enterprise and domain-specific data assets.
• Design information architecture incorporating data classification, privacy, security, and regulatory requirements.
• Establish sustainable enterprise data architecture patterns.

2. Modernization Programs

• Partner with workflow modernization teams to incorporate reusable data products into solution designs.
• Analyze legacy systems and identify information assets suitable for enterprise reuse.
• Prevent duplication of data structures across applications and business domains.
• Support data migration strategies and target-state architecture.
• Contribute to enterprise digital transformation initiatives.

3. Data Product Architecture

• Identify and support the design of reusable data products.
• Define schemas, interfaces, metadata, and data quality requirements.
• Establish product boundaries, stewardship, and ownership models.
• Promote reusable and scalable data architecture patterns.

4. Data Governance and Metadata

• Establish data architecture principles, standards, best practices, and guidelines.
• Support data cataloging, lineage, observability, security, and interoperability.
• Define business data definitions and quality expectations.
• Promote consistent metadata and ownership standards.

5. Platform and Technology Collaboration

• Work with engineering and platform teams to translate business concepts into technical designs.
• Partner with cloud, integration, and data teams to implement enterprise data products.
• Promote API-first and product-based approaches to information sharing.
• Support cloud-based data platform initiatives.

6. AI Enablement

• Ensure enterprise data products are discoverable, governed, and suitable for future AI use cases.
• Support semantic layers, knowledge graphs, and natural-language access to enterprise information.
• Establish data architecture patterns that enable analytics and AI initiatives.

Desired Background and Experience

• Bachelor's degree in Computer Science, Information Systems, Systems Programming, or a related field, or an equivalent combination of education and experience.
• Minimum 10 years of experience in data architecture, information architecture, or enterprise architecture.
• 8+ years of hands on experience in data architecture, data engineering, or advanced database design and modeling.
• Experience designing or implementing data warehouses and data marts.
• Experience with Master Data Management (MDM) concepts and tools.
• At least 5 years of experience with modern data platforms such as Snowflake, Databricks, MongoDB, and cloud-based ecosystems including AWS, Azure, or GCP.
• Experience working with unstructured data is a plus.
• Experience with data security, privacy, and regulatory requirements for sensitive data.
• Experience designing and implementing data quality initiatives, platforms, and tooling.
• Demonstrated experience supporting large-scale modernization or digital transformation initiatives across multiple domains and stakeholders.
• Strong communication and collaboration skills with the ability to work across technical and business domains.
• Ability to develop work plans, resolve ambiguity, and lead teams through influence rather than direct authority.
• Experience in public sector, healthcare, or financial services is preferred.
• Previous experience as a Principal Architect, Enterprise Information Architect, or Solution Architect supporting large enterprises or modernization initiatives is preferred.

Key Skills

• Enterprise Data Architecture
• Information Architecture
• Data Modeling
• Data Warehousing & Data Marts
• Master Data Management (MDM)
• Data Governance
• Data Quality
• Metadata Management
• Data Lineage & Cataloging
• Data Security & Privacy
• Snowflake
• Databricks
• MongoDB
• AWS / Azure / GCP
• Cloud Data Architecture
• Data Products
• API-First Architecture
• Data Migration
• Legacy Modernization
• Semantic Layers
• Knowledge Graphs
• AI-Ready Data Architecture
• Stakeholder Management
Enterprise Architecture

Success Measures

During the first year, the successful candidate will:

• Establish enterprise information architecture principles and standards.
• Define reusable enterprise data products for priority domains.
• Support modernization initiatives through practical implementation of enterprise data architecture.
• Introduce metadata, data quality, stewardship, and ownership standards.
• Enable future modernization efforts to reuse common data assets rather than creating redundant data structures.
• Establish a strong foundation for enterprise analytics and AI capabilities.