- Company Name
- Dayforce
- Job Title
- Sr. Director, Enterprise Data and AI Platform
- Job Description
-
**Job Title:** Sr. Director, Enterprise Data and AI Platform
**Role Summary:**
Lead global enterprise data and AI strategy, architecture, and execution. Drive platform design on Azure, oversee data engineering, advanced analytics, and Agentic AI initiatives, and ensure data governance, security, and vendor management to support enterprise business functions.
**Expectations:**
- Visionary leader with deep technical expertise in modern data and AI.
- Proven ability to manage and scale global teams, budgets, and vendor portfolios.
- Strong partnership with senior business leaders to translate data strategy into actionable outcomes.
- Hands‑on technical capability to guide architecture, integration, and model deployment at scale.
**Key Responsibilities:**
- Define and execute enterprise data architecture strategy (Azure Data Lake, Synapse, Data Factory, Data Fabric).
- Lead a global Data & AI engineering team, setting talent, processes, and performance metrics.
- Own data pipelines, product delivery, and data asset lifecycle for enterprise reporting, analytics, and ML.
- Architect, select, pilot, and implement Agentic AI capabilities; build AI Platform Center of Excellence.
- Partner with business leaders to enable data‑driven decisions and advanced analytics.
- Establish data governance, security standards, and SLA enforcement.
- Manage platform budgets, third‑party vendor contracts, and architecture governance (ARB).
- Apply MLOps best practices for model monitoring, retraining, and lifecycle management.
- Champion Agile and SAFe methodologies across cross‑functional delivery teams.
**Required Skills:**
- Azure cloud, Data Lake/Warehouse/Mesh, Data Fabric, Power BI, Tableau, data integration tools.
- Deep knowledge of MLOps, statistical modeling, NLP, computer vision, deep learning (PyTorch, TensorFlow, Hugging Face).
- Experience building cross‑functional enterprise data warehouses and deploying models at scale.
- Familiarity with Agentic AI platforms (e.g., Replit, Vercel).
- Strong business partnership, change management, and cross‑functional collaboration abilities.
- Proven project, budget, and vendor management in a global environment.
- Leadership of Data & ML Engineering or Analytics teams.
**Required Education & Certifications:**
- Advanced degree (Master’s or Ph.D.) in Computer Science, Data Science, Machine Learning, or related field preferable.
- Minimum 10 years of senior enterprise data and AI leadership experience.
- Certifications in Azure, Data Engineering, or AI/ML (e.g., Microsoft Azure Data Engineer, Azure AI Engineer, or equivalent) are a plus.