Job Description

About the opportunity 

We are seeking a strategic and hands-on Senior Data Architect to design, optimize, and scale our enterprise data architecture at Dayforce. This role will lead the design and governance of the data ecosystem—spanning integrations, modeling, storage, and engineering—within the Enterprise Data Center of Excellence. The Senior Data Architect will collaborate across technology and business functions to enable a data-driven culture and accelerate our cloud transformation.

This is a high-impact role within a fast-evolving, global organization. The ideal candidate is an experienced architect with strong consultative skills, a passion for innovation, and a proven ability to guide enterprises through modernization—from on-premise to cloud-native data platforms.

This position reports to the Sr. Director, Enterprise Data and AI Platform.

What you'll get to do

Enterprise Data Architecture & Strategy

Lead the design, development, and implementation of scalable enterprise data architectures.
Establish and enforce data modeling, integration, and engineering standards across the organization.
Partner with business and technical stakeholders to define the long-term data strategy aligned with enterprise goals.
Conduct research on emerging technologies, tools, and industry trends to drive continuous innovation.

Data Platform Design & Engineering

Architect and manage modern data platforms—leveraging cloud-native services for performance, reliability, and scalability.
Develop and optimize data models, schemas, and pipelines to support analytics, reporting, and AI/ML initiatives.
Oversee data integration patterns (batch, streaming, API-led) to ensure consistent and accurate data flow.
Evaluate, recommend, and select platform components and tools for enterprise data management.

Governance, Quality & Performance

Define and implement data governance, quality, and security frameworks to ensure data integrity and compliance.
Monitor system performance and proactively optimize configurations, pipelines, and storage for efficiency.
Diagnose and resolve complex data performance, access, and consistency issues.

Collaboration & Enablement

Partner with Data Engineering, Analytics, and AI teams to enable data-driven decision-making.
Collaborate with cross-functional teams to ensure data availability, protection, and alignment with business needs.
Participate in the Architecture review board process and present new data initiatives.
Contribute to knowledge sharing and mentoring within the Data & AI organization. 

Skills and experience we value

Bachelor’s degree in Computer Science, Information Systems, or related field (Master’s degree preferred).
7+ years of experience in data engineering, architecture, or data platform design roles.
Proven experience leading or architecting cloud data modernization initiatives.
Deep expertise across Azure Data Lake Storage (ADLS Gen2), Data Factory, Synapse, Microsoft Fabric, Databricks, Azure Machine Learning, and Azure AI Foundry. Proven experience provisioning, administering, and operating complex, large-scale cloud data platforms.
Hands-on experience with Azure Functions, Web Apps, Static Web Apps, Container Apps, Azure Container Registry (ACR), Logic Apps, App Service Plans, and Azure Virtual Machines. Skilled in designing and managing cloud network architectures including VNets, DNS, NSGs, and private endpoints.
Strong background in designing and building data pipelines, API-led architectures, and enterprise data models. Skilled in creating, maintaining, and optimizing end-to-end data solutions aligned with data warehousing best practices and scalability principles.
Proficiency in SQL, Python, Spark, and KQL, with a focus on performance, scalability, and maintainability.
Experienced in implementing RBAC and ABAC-based workload designs, Privileged Identity Management (PIM), and Just-in-Time (JIT) access controls. Adept at applying best practices for auditability, observability, and platform analytics in enterprise environments.
Expertise in Power BI and Microsoft Fabric administration, with a deep understanding of Fabric architecture—including OneLake, Lakehouse, Warehouse, and Spark. Strong grasp of ML/AI capabilities and experience delivering end-to-end solutions on Fabric.
Exposure to advanced AI solution patterns including vector embeddings, retrieval-augmented generation (RAG), multi-component pipelines (MCP), and agentic AI architectures.
Hands-on experience managing enterprise projects, repositories, and user permissions, building CI/CD pipelines using Azure Pipelines or GitHub Actions, and administering agent pools and service connections. Applies Site Reliability Engineering (SRE) principles for resilient and automated operations.
Proven ability to deliver high-quality solutions in Agile and DevOps environments, collaborating closely with cross-functional teams.
Familiarity with cloud ecosystems such as AWS and Google Cloud Platform (GCP).
Strong communication and stakeholder management abilities.
Demonstrated ability to influence enterprise architecture and technical decisions.
Consultative, collaborative, and growth-oriented mindset.