Enterprise Data Architect – AI Readiness / Data Transformation

Description

Our client, a leader in their industry, has an excellent opportunity for an Enterprise Data Architect to support a major enterprise data transformation focused on AI readiness, data quality, governance, and enterprise-wide data modernization.

This is a 6–12 month contract-to-hire opportunity. The role is fully remote.

Contract Rate: $90–$100/hr W-2

Conversion Salary: Approximately $180K base + 20% bonus

This is not a traditional architecture role. The organization is preparing its data ecosystem to support future AI, machine learning, analytics, personalization, and enterprise reporting initiatives. This person will help drive the transformation needed to make enterprise data cleaner, more connected, better governed, and usable at scale.

The ideal candidate must be able to drive change across siloed teams, influence leadership, establish alignment, and move data initiatives forward in a complex environment. This is not a hands-on

keyboard engineering role. The focus is on enterprise data strategy, architecture, influence, governance, and execution leadership.

If you prefer clearly defined ownership, purely technical design work, or staying within your lane, this will not be the right fit. This role requires someone who can challenge stakeholders, create momentum, and lead data transformation across the organization without always having direct authority.

Due to client requirements, applicants must be willing and able to work on a W-2 basis. For our W-2 consultants, we offer a benefits package that includes Medical, Dental, Vision, 401(k) with company matching, and life insurance.

Responsibilities

• Lead enterprise data architecture and data transformation efforts focused on AI readiness, data quality, governance, and enterprise data usability.
• Assess the current data landscape and identify gaps that limit the organization’s ability to support AI, ML, analytics, reporting, and future digital initiatives.
• Create actionable roadmaps to improve data health, reduce fragmentation, and prepare enterprise data for advanced analytics and AI use cases.
• Drive alignment across siloed business and technology teams to establish consistent data models, data flows, ownership, standards, and governance.
• Partner with senior leaders, business stakeholders, and technology teams to improve enterprise data strategy and execution.
• Influence teams without direct authority and help move cross-functional data initiatives forward.
• Define and evolve data architecture standards, integration patterns, governance frameworks, and data management best practices.
• Support enterprise data architecture across platforms including Google Cloud Platform, Salesforce, AWS, and on-prem environments.
• Evaluate current-state data platforms, tools, and processes and recommend modernization or migration strategies.
• Lead cross-functional discussions, remove roadblocks, and help accelerate data initiatives tied to AI readiness and enterprise transformation.
• Present findings, recommendations, roadmaps, and progress updates to senior leadership.

Experience Requirements

• 10+ years of IT experience, including 3–5+ years in a Data Architect, Enterprise Data Architect, or similar leadership role.
• Proven experience leading enterprise data transformation, data modernization, or large-scale data readiness initiatives.
• Strong understanding of what it takes to prepare enterprise data for AI, ML, advanced analytics, and scalable reporting.
• Demonstrated experience improving data quality, governance, data ownership, and overall enterprise data health.
• Proven ability to influence stakeholders, gain buy-in, and drive adoption across complex, siloed organizations.
• Strong experience in data architecture, data warehousing, enterprise data integration, and data modeling.
• Strong experience with Google Cloud Platform, especially BigQuery, data pipelines, or large-scale cloud data platforms.
• Experience working with Salesforce data integration, AWS, or other cloud platforms is a plus.
• Prior hands-on background in data-related ETL, data integration, APIs, microservices architecture, or enterprise application/data flows.
• Experience with relational databases, NoSQL databases, BI tools, and big data technologies.
• Ability to communicate clearly with both technical and executive audiences.

Preferred Skills

• Experience with large-scale consumer data environments.
• Experience supporting AI/ML, personalization, customer data, or advanced analytics initiatives.
• Experience improving enterprise data quality, governance, lineage, metadata, or master data practices.
• Familiarity with tools such as Tableau, Power BI, Looker, or similar BI/reporting platforms.
• Experience working in environments with Salesforce, customer data platforms, marketing data, loyalty data, or digital product data.

This Role Is NOT For Someone Who

• Wants a purely hands-on engineering or development role.
• Has only designed architecture but has not driven adoption or organizational change.
• Needs formal authority to influence teams and move work forward.
• Is uncomfortable challenging stakeholders or pushing initiatives through ambiguity.
• Prefers a narrow lane with clearly defined ownership and limited cross-functional complexity.

Education Requirements

Bachelor’s or Master’s Degree in a relevant field of work, or an equivalent combination of education and work-related experience.