Enterprise Data Architect

FutureSoft Consulting Inc • Harrisburg, PA

1d • Hybrid

About The Position

We are seeking an experienced Enterprise Data Architect to lead the design and evolution of enterprise information architecture and reusable data products supporting large-scale modernization, analytics, and AI initiatives. The ideal candidate will bring deep expertise in enterprise data architecture, information modeling, cloud data platforms, data governance, data quality, and modernization. This individual will work closely with business leaders, product teams, engineers, data teams, and technology stakeholders to establish a sustainable enterprise data foundation while reducing duplication and data silos. This is a senior-level architecture position requiring both strategic leadership and hands-on experience designing complex enterprise data environments.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Systems Programming, Engineering, or a related discipline, or an equivalent combination of education and professional experience.
• 10+ years of experience in Data Architecture, Information Architecture, or Enterprise Architecture.
• 8+ years of hands-on experience in data architecture, data engineering, advanced database design, and data modeling.
• Strong experience designing or implementing data warehouses and data marts.
• Experience with Master Data Management (MDM) concepts, architectures, and tools.
• 5+ years of experience working with modern data platforms such as: Snowflake, Databricks, MongoDB.
• Strong experience with cloud-based data ecosystems using AWS, Azure, and/or GCP.
• Experience designing conceptual, logical, and enterprise data models.
• Experience with enterprise data governance, metadata management, data lineage, and data cataloging.
• Experience developing and implementing enterprise data quality initiatives and associated platforms/tools.
• Strong knowledge of data security, privacy, and regulatory requirements involving sensitive information.
• Demonstrated experience supporting large-scale modernization or digital transformation initiatives involving multiple domains and stakeholders.
• Strong understanding of enterprise integration and API-based architectures.
• Excellent communication, documentation, stakeholder management, and presentation skills.
• Ability to operate independently, resolve ambiguity, develop work plans, and influence teams without direct authority.

Nice To Haves

• Previous experience as an Enterprise Data Architect, Enterprise Information Architect, Principal Data Architect, Principal Architect, Data Solution Architect, or Enterprise Solution Architect.
• Experience in public sector, healthcare, or financial services environments.
• Experience working with unstructured data.
• Experience implementing reusable enterprise data products.
• Knowledge of data contracts and data-product architectures.
• Experience with semantic models or semantic layers.
• Knowledge of knowledge graphs and enterprise ontology concepts.
• Experience supporting data platforms designed for AI, machine learning, or generative AI applications.

Responsibilities

• Define conceptual and logical data models for enterprise business entities.
• Develop canonical data models and enterprise information standards.
• Establish relationships between enterprise-wide and domain-specific data assets.
• Design information architecture incorporating data security, privacy, classification, and regulatory requirements.
• Define enterprise data architecture principles, standards, patterns, and best practices.
• Support large-scale application and data modernization initiatives.
• Analyze legacy systems and identify data assets suitable for enterprise reuse.
• Develop source-to-target and source-to-domain data mappings.
• Support data migration strategies and target-state architecture.
• Prevent unnecessary duplication of data structures across systems and business domains.
• Design and support data warehouses, data marts, and modern data architectures.
• Identify opportunities to create reusable enterprise data products.
• Define schemas, interfaces, metadata, data contracts, and quality requirements.
• Establish appropriate boundaries, ownership, and stewardship models for data products.
• Promote API-first and product-oriented approaches to enterprise information sharing.
• Establish standards for data governance, metadata management, data catalogs, data lineage, data observability, data interoperability, data security, and data quality.
• Define business data definitions and enterprise data quality expectations.
• Partner with governance and business teams to establish ownership and stewardship standards.
• Support implementation of data quality platforms and tooling.
• Collaborate with cloud, platform, integration, and engineering teams to translate business requirements into scalable technical solutions.
• Architect solutions using modern data platforms such as Snowflake, Databricks, and MongoDB.
• Support enterprise data environments across AWS, Microsoft Azure, and/or Google Cloud Platform (GCP).
• Work with structured, semi-structured, and unstructured enterprise data.
• Ensure enterprise data products are discoverable, governed, secure, and suitable for AI and advanced analytics use cases.
• Help establish the data foundation required for enterprise AI initiatives.
• Support development of semantic layers, knowledge graphs, and natural-language access to enterprise information.
• Collaborate with analytics and AI teams to ensure data architecture supports future machine learning and generative AI capabilities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior