Data Architect

Job not on LinkedIn

🔥 2 hours ago

⚔️ Virginia – Remote

⚔️ Virginia – Remote

💵 $118.8k - $178.2k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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Dayforce

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

👥 HR Tech

☁️ SaaS

🏢 Enterprise

💰 $1G Post-IPO Debt - Dayforce on 2024-03

HR Tech • SaaS • Enterprise

Dayforce is a cloud-based human capital management (HCM) platform that provides payroll, workforce management, time and attendance, benefits administration, talent management, and HR tools as an integrated SaaS solution for employers. It is designed to help organizations manage payroll, scheduling, compliance, and employee lifecycle processes in a single unified application.

📋 Description

• Define and maintain the target-state architecture for the Unified Data Layer, including landing, curated, and semantic layers. • Develop architecture principles for modularity, interoperability, reusability, and governance across business and operational data domains. • Serve as the design authority for major data platform and integration decisions. • Design enterprise and domain-level canonical models for key entities such as material, product, asset, equipment, work order, batch, vendor, customer, cost center, logistics shipment, quality event, and energy usage. • Define standards for dimensional modeling, semantic modeling, event models, and reference data structures. • Define architectural patterns for ingesting and harmonizing data from multiple enterprise platforms into the Unified Data Layer. • Lead design reviews for new data products, major source integrations, and semantic layer changes. • Produce architecture diagrams, conceptual and logical data models, reference patterns, and design standards.

🎯 Requirements

• Minimum 8 years' of experience in enterprise data architecture, data modeling, and large-scale data platform design. • Proven experience designing lakehouse or enterprise data platform architectures across multiple domains. • Strong expertise in conceptual, logical, and physical data modeling, dimensional modeling, semantic layer design, and canonical data structures. • Strong understanding of Azure-based data architectures, including Databricks or Fabric and Synapse, ADLS or OneLake, Data Factory or pipelines, and integration with Power BI. • Working knowledge of SAP S4 HANA data structures and SAP DataSphere semantic concepts. • Familiarity with OT and industrial data patterns, including historians, event frames, asset hierarchies, time-series data, and ISA-based structures. • Strong knowledge of data contracts, schema versioning, lineage, master data alignment, and architecture governance. • Excellent communication skills with the ability to translate architecture into clear implementation guidance.