Data Architect Lead

Agentic Dream is seeking a highly skilled Data Architect Lead. This transformative initiative focuses on unifying fragmented data systems into a centralized, AI-enabled data platform.

As a Data Architect Lead, you will play a key role in designing and delivering scalable, analytics‑ready architecture that integrates data from 11+ ERP systems (Net Suite, Salesforce, SAP, Quick Books, and more). This position demands strong technical acumen, hands‑on leadership, and the ability to drive delivery across cross‑functional teams, often under tight deadlines. You’ll work in close collaboration with PMs, POs, and global stakeholders, primarily based in the U.S.

This is a high-impact opportunity for someone looking to architect data ecosystems that power enterprise‑wide decision‑making and AI‑driven insights.

Learn more about us at:

• 8+ years in data architecture, data engineering, or similar roles within enterprise environments.
• Proven experience integrating multiple ERP systems (Net Suite, SAP, Quick Books, Salesforce, etc.).
• Advanced proficiency in SQL, ETL design, and data modeling (star/snowflake schemas).
• Strong command of cloud‑based data platforms, especially Microsoft Azure.
• Demonstrated expertise in Master Data Management (MDM) and data governance frameworks.
• Experience deploying AI/ML models for reporting, forecasting, or anomaly detection.
• Excellent English communication skills (C1 level), including stakeholder‑facing experience.
• Strong leadership in managing developers, analysts, and delivery teams.
• Willingness to align working hours with U.S. EST and occasionally work extended hours.

• Architectural Design & Delivery:
  Lead the design and execution of data lakes, warehouses, and transformation pipelines across multiple ERP systems.
• ETL Strategy:
  Define robust strategies to ingest, cleanse, harmonize, and model master data from fragmented sources.
• Master Data Governance:
  Establish master data standards, naming conventions, validation rules, and enforce data quality protocols.
• Data Modeling:
  Develop scalable enterprise models for sales, orders, inventory (SKU, BOM), and labor data.
• AI Enablement:
  Support AI‑driven tools for demand forecasting, margin analysis, and productivity insights.
• Stakeholder
  
  Collaboration:
  
  Engage regularly with business users, PMs, and POs to align data architecture with business goals.
• Team Leadership:
  Provide hands‑on technical leadership to developers, analysts, and QA to ensure scalability, performance, and security standards are met.
• Documentation & Delivery:
  Produce ERDs, transformation logic, and change logs for technical handoff and production deployment.
• Workshop Facilitation:
  Conduct architecture reviews and stakeholder workshops to iterate and refine delivery approach.