• Design end-to-end data architectures, defining ingestion, transformation, and curation patterns that support analytics and AI workloads • Ensure efficient replication, synchronization, and data flow across Fabric workspaces and multi-zone environments • Ensure all data architectures align with Microsoft’s Cloud Adoption Framework (CAF) and the Azure Well-Architected Framework • Partner with stakeholders to understand reporting, analytics, and AI needs and design scalable, flexible data models • Define structures, metadata, and access patterns for data discoverability and usability for AI workloads • Collaborate with peers to implement encryption, role-based access controls, and data masking • Guide architecture decisions related to Fabric SKUs and data refresh strategies • Work closely with Data Engineers to translate architecture into delivery and promote data quality • Produce reference architectures, blueprints, and reusable standards for future projects

• Define and implement the company’s data architecture, models, and pipelines. • Design integrations between internal platforms and third-party systems (Salesforce, CX platforms, etc.). • Establish standards for data quality, metadata, lineage, and classification. • Partner with engineering, security, and compliance teams to align on privacy, retention, and access control policies. • Lead the selection and implementation of data platforms. • Drive adoption of data best practices across teams and support data governance efforts. • Support data risk reviews, vendor onboarding, and audit readiness from a technical standpoint. • Maintain data platforms and architecture performance. • Support existing data workflows, and integrations. • Respond to data-related incidents and ensure data reliability. • Improve data models to support business growth and analytics. • Optimize data pipelines, quality, and availability. • Expand self-service data capabilities for stakeholders. • Define future-state architecture to enable digital transformation. • Lead data strategy to support AI/ML, automation and advanced analytics. • Integrate data across new platforms, partners, or business models.

• Drive the end-to-end implementation of Microsoft Fabric across the organization • Lead the setup of ETL/ELT pipelines • Design and implement the bronze, silver, and gold layers of our data Lakehouse • Oversee the configuration of key Fabric components including Data Factory, One Lake, and Power BI • Explore advanced capabilities such as Microsoft Copilot to accelerate analytics and automation • Collaborate with the D&A team and business stakeholders to translate business needs into scalable data architecture • Define and implement a modern data Lakehouse framework using Microsoft Fabric • Engage with executives and functional leaders to establish metrics, strategies, and implement roadmaps for enterprise-wide analytics

• Design and implement GenAI-based solutions that optimize critical stages of the DDLC (Data Development Life Cycle). • Develop agents that act as assistants in creating Databricks notebooks, pipelines in ADF, and structures in Microsoft Fabric. • Create workflows that integrate LLMs into our ecosystem (SQL Server and Power BI), automating tasks such as data documentation and creation of DAX measures. • Apply advanced prompt engineering techniques to ensure the AI generates optimized, secure, and high-performance PySpark and T-SQL code. • Define quality metrics to validate AI-generated artifacts (e.g., ensure efficiency of generated queries). • Ensure solutions align with Data Governance, security, and privacy practices. • Stay up to date on AI capabilities within Microsoft Fabric and Databricks to maximize the use of native tools versus custom developments.