Enterprise Data & AI Architect

JOB TITLE: Enterprise Data & AI Architect

DEPARTMENT: Information Technology

REPORTS TO: CITO

FLSA STATUS: Exempt

Bay Cities, an Employee-Owned Company, is the leading creative packaging and display partner to brand marketers, retailers and e-commerce. Our passion, experience, technology, and consumer insights move product and drive sales.

Our Mission

Our Passion Powers Your Product

Our Values

Creativity: Our ideas create Client success.

Passion: We have heart with a Customer Service attitude.

Integrity: We honor our business & planet with sustainable practices.

Responsible: We own it!

Safe: Our safe work habits protect us all.

Fun: We take our work seriously- not ourselves

SUMMARY

Bay Cities Container has an exciting opportunity for an Enterprise Data & AI Architect for a remote based position. Bay Cities is located in Southern California (Greater Los Angeles area) and is seeking an Enterprise Data & AI Architect to either work remotely or on site. The ideal candidate will live anywhere in the United States but have the ability to travel to our corporate location as needed. Bay Cities is an Employee Owned (ESOP) corrugated packaging and display manufacturer. We design, manufacture, and deliver custom packaging, point-of-purchase displays, and fulfillment solutions for major national brands. We are in the middle of a CEO sponsored digital transformation- building an enterprise intelligence platform that connect our manufacturing, financial, sales, and operational systems through modern data architecture and AI. This is not a planning exercise. We have a functioning platform with proven results already in production.

The Role

We are hiring an Enterprise Data & AI Architect to own and extend the data intelligence and AI automation platform that drives our business transformation. You will report directly to the CIO and lead a small BI/analytics team (3-4 members).

This is a hands-on technical leadership role. You will write SQL, build semantic models, design data pipelines, configure AI-assisted workflows, and deliver measurable business outcomes- not just draw architecture diagrams. You'll inherit a functioning platform with real production workloads and be expected to keep it running while expanding its capabilities.

What You'll Do

Data Architecture & Warehousing

• Own and extend a SQL Server analytics data warehouse with dimensional modeling (star schema, conformed dimensions, fact/dimension tables).
• Design and maintain data pipelines from multiple legacy source systems (ERP, logistics, workflow management) through to Microsoft Fabric.
• Handle complex temporal data challenges- reconciling multiple systems with incompatible time grains.
• Maintain schema governance, documentation, and data lineage.

Business Intelligence & Reporting

• Build and maintain Power BI semantic models deployed to Microsoft Fabric.
• Develop DAX measure libraries for financial and operational reporting.
• Deliver executive dashboards- P&L, Balance Sheet, Flash Reports, cost analysis, operational metrics.
• Ensure data quality through validation and reconciliation between source systems and reporting layers.

AI & Automation

• Design and orchestrate AI agent workflows for business process automation.
• Build workflow automations for data pipelines, alerting, and system integration.
• Implement agent-assisted analytics- where AI investigates, subject matter experts validate, and the system learns.
• Manage prompt engineering, AI governance, and safety boundaries for production AI systems.

Manufacturing Cost Intelligence

• Work with legacy ERP cost models (Activity-Based Costing, BOM structures, GL interaction).
• Build margin analysis, vendor spend tracking, and cost-per-unit modeling.
• Reconcile estimated costs against actuals across multiple systems.

Stakeholder Delivery

• Translate business needs from executives (CFO, CRO, COO) into data products.
• Manage a portfolio of concurrent analytics projects from intake through delivery.
• Deliver iteratively- prove value in days, not months.

Team Leadership

• Lead and mentor a small BI/Analytics team.
• Distribute work to eliminate single-person bottlenecks and knowledge concentration.
• Build team capability so institutional knowledge compounds across people, not in one person.
• Ensure IT governance: proper secrets management, access controls, and security practices.