10-15 years of experience in data architecture and design
Deep expertise in modern data architecture patterns
Strong focus on AI and data strategy development
Proven ability to articulate a forward-looking data vision
Experience with data governance and compliance standards
Responsibilities
Define and build comprehensive data architecture and strategy
Design and maintain data models for core business services
Create data flow diagrams and orchestration strategies
Collaborate with Application and Cloud Architects for system alignment
Develop evaluation criteria for selecting data architecture components
Evolve data governance policies and best practices
Provide technical oversight and mentorship to data teams
Benefits
4 days onsite work schedule
Opportunity to lead and influence data strategy
Engagement with cutting-edge technologies in AI and data architecture
Collaborative work environment with cross-functional teams
Professional development and mentorship opportunities
Full Job Description
Job Title; Data Architect
Location :Hartford, CT / Minneapolis, MN
Job Description
Location: Hartford, CT OR Minneapolis, MN (This is a 4 days onsite role).
A thought leader who can define and build out the components of a comprehensive data strategy and architecture with a strong focus on AI.
This person should have deep expertise in modern data architecture patterns and the ability to articulate a clear, forward-looking vision.
The Data Architect delivers the data vision and strategy for the organization, as defined by the Chief Data Architect (or equivalent leadership).
This role is responsible for the design, governance, and technical oversight of the enterprise data architecture, ensuring that data systems are scalable, secure, compliant, and aligned with core business needs.
Key Responsibilities
Data Architecture & Design
Data Modeling: Design, maintain, and evolve comprehensive data models (Conceptual, Logical, and Physical) for core business services and platforms.
Data Flow: Define and create data flow diagrams and orchestration strategies, ensuring efficient and governed data movement between upstream and downstream systems.
System Alignment: Collaborate closely with Application and Cloud Architects to ensure the organization's technical systems are designed to fully support the established data architecture standards.
Technology Selection: Develop product short-lists and evaluation criteria for selecting data architecture components, such as data warehousing solutions, Big Data platforms (e.g., Hadoop, Spark, Kafka), and database technologies (SQL/NoSQL).
Data Governance & Quality
Governance Frameworks: Evolve and define data governance policies, standards, and best practices across the organization.
Metadata Management: Design, support, and manage data dictionaries, metadata repositories, and common entities to ensure consistent use and definition of data.
Data Quality: Drive the standards for Data Quality across multiple datasets, ensuring consistency and data trust across the enterprise.
Compliance: Design data retention, upgrade, management, decommission, and archive strategies in compliance with data policies and regulatory standards (e.g., data privacy).
Technical Leadership & Mentorship
Oversight: Provide technical oversight, advice, and guidance to other Data Architects, Data Engineers, and development teams regarding data structures and associated components.
