Data Architect – AI & Data Strategy

Job Description: Data Architect – AI & Data Strategy

Location: Hartford, CT or Minneapolis, MN

12+months Contract

Work Model: 4 days onsite

Job Summary

A thought leader who can define and build out the components of a comprehensive data strategy and architecture, with a strong focus on AI. The ideal candidate 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

1. 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 fully support established data architecture standards.
• Technology Selection: Develop product shortlists and evaluation criteria for selecting data architecture components, including data warehousing solutions, Big Data platforms (e.g., Hadoop, Spark, Kafka), and database technologies (SQL/NoSQL).

2. 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 data quality standards across multiple datasets, ensuring consistency and trust in enterprise data.
• Compliance: Design data retention, upgrade, management, decommissioning, and archiving strategies in compliance with data policies and regulatory standards, including data privacy requirements.

3. Technical Leadership & Mentorship

• Technical Oversight: Provide technical oversight, advice, and guidance to other Data Architects, Data Engineers, and development teams regarding data structures and associated components.